cons_bivariate.c
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17 * @brief constraint handler for bivariate nonlinear constraints \f$\textrm{lhs} \leq f(x,y) + c z \leq \textrm{rhs}\f$
23 /*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
70 #define CONSHDLR_DESC "constraint handler for constraints of the form lhs <= f(x,y) + c*z <= rhs where f(x,y) is a bivariate function"
72 #define CONSHDLR_ENFOPRIORITY -55 /**< priority of the constraint handler for constraint enforcing */
73 #define CONSHDLR_CHECKPRIORITY -3600000 /**< priority of the constraint handler for checking feasibility */
74 #define CONSHDLR_SEPAFREQ 1 /**< frequency for separating cuts; zero means to separate only in the root node */
75 #define CONSHDLR_PROPFREQ 1 /**< frequency for propagating domains; zero means only preprocessing propagation */
76 #define CONSHDLR_EAGERFREQ 100 /**< frequency for using all instead of only the useful constraints in separation,
78 #define CONSHDLR_MAXPREROUNDS -1 /**< maximal number of presolving rounds the constraint handler participates in (-1: no limit) */
79 #define CONSHDLR_DELAYSEPA FALSE /**< should separation method be delayed, if other separators found cuts? */
80 #define CONSHDLR_DELAYPROP FALSE /**< should propagation method be delayed, if other propagators found reductions? */
81 #define CONSHDLR_NEEDSCONS TRUE /**< should the constraint handler be skipped, if no constraints are available? */
88 #define INITLPMAXVARVAL 1000.0 /**< maximal absolute value of variable for still generating a linearization cut at that point in initlp */
90 #define QUADCONSUPGD_PRIORITY 5000 /**< priority of the constraint handler for upgrading of quadratic constraints */
91 #define NONLINCONSUPGD_PRIORITY 10000 /**< priority of the constraint handler for upgrading of nonlinear constraints */
93 /* activate the following define to get output on number of bivariate constraints for each convexity-type during INITSOL */
128 unsigned int mayincreasez:1; /**< whether z can be increased without harming other constraints */
129 unsigned int maydecreasez:1; /**< whether z can be decreased without harming other constraints */
132 SCIP_EXPRGRAPHNODE* exprgraphnode; /**< node in expression graph corresponding to bivariate function */
134 SEPADATA_CONVEXCONCAVE sepaconvexconcave; /**< separation data for convex-concave constraints */
142 SCIP_Real cutmaxrange; /**< maximal range (maximal coef / minimal coef) of a cut in order to be added to LP */
144 int maxproprounds; /**< limit on number of propagation rounds for a single constraint within one round of SCIP propagation */
145 int ninitlprefpoints; /**< number of reference points in each direction where to compute linear support for envelope in LP initialization */
146 SCIP_Bool enfocutsremovable; /**< are cuts added during enforcement removable from the LP in the same node? */
155 SCIP_Bool isremovedfixings; /**< whether variable fixations have been removed from the expression graph */
156 SCIP_Bool ispropagated; /**< whether the bounds on the variables in the expression graph have been propagated */
159 SCIP_NODE* lastenfonode; /**< the node for which enforcement was called the last time (and some constraint was violated) */
177 {
225 /* if right hand side is finite, then a tightening in the lower bound of coef*linvar is of interest */
233 /* if left hand side is finite, then a tightening in the upper bound of coef*linvar is of interest */
240 SCIP_CALL( SCIPcatchVarEvent(scip, consdata->z, eventtype, conshdlrdata->linvareventhdlr, (SCIP_EVENTDATA*)cons, &consdata->eventfilterpos) );
277 /* if right hand side is finite, then a tightening in the lower bound of coef*linvar is of interest */
285 /* if left hand side is finite, then a tightening in the upper bound of coef*linvar is of interest */
292 SCIP_CALL( SCIPdropVarEvent(scip, consdata->z, eventtype, conshdlrdata->linvareventhdlr, (SCIP_EVENTDATA*)cons, consdata->eventfilterpos) );
302 {
322 SCIPvarGetName(SCIPeventGetVar(event)), SCIPeventGetOldbound(event), SCIPeventGetNewbound(event));
349 {
365 SCIP_CALL( SCIPcatchVarEvent(conshdlrdata->scip, (SCIP_VAR*)var, SCIP_EVENTTYPE_BOUNDCHANGED | SCIP_EVENTTYPE_VARFIXED, conshdlrdata->nonlinvareventhdlr, (SCIP_EVENTDATA*)varnode, NULL) );
366 SCIPdebugMessage("catch boundchange events on new expression graph variable <%s>\n", SCIPvarGetName(var_));
370 -infty2infty(SCIPinfinity(conshdlrdata->scip), INTERVALINFTY, -MIN(SCIPvarGetLbLocal(var_), SCIPvarGetUbLocal(var_))), /*lint !e666*/
371 +infty2infty(SCIPinfinity(conshdlrdata->scip), INTERVALINFTY, MAX(SCIPvarGetLbLocal(var_), SCIPvarGetUbLocal(var_))) /*lint !e666*/
387 {
401 SCIP_CALL( SCIPdropVarEvent(conshdlrdata->scip, var_, SCIP_EVENTTYPE_BOUNDCHANGED | SCIP_EVENTTYPE_VARFIXED, conshdlrdata->nonlinvareventhdlr, (SCIP_EVENTDATA*)varnode, -1) );
402 SCIPdebugMessage("drop boundchange events on expression graph variable <%s>\n", SCIPvarGetName(var_));
431 SCIP_CALL( SCIPlockVarCons(scip, var, cons, !SCIPisInfinity(scip, -consdata->lhs), !SCIPisInfinity(scip, consdata->rhs)) );
435 SCIP_CALL( SCIPlockVarCons(scip, var, cons, !SCIPisInfinity(scip, consdata->rhs), !SCIPisInfinity(scip, -consdata->lhs)) );
462 SCIP_CALL( SCIPunlockVarCons(scip, var, cons, !SCIPisInfinity(scip, -consdata->lhs), !SCIPisInfinity(scip, consdata->rhs)) );
466 SCIP_CALL( SCIPunlockVarCons(scip, var, cons, !SCIPisInfinity(scip, consdata->rhs), !SCIPisInfinity(scip, -consdata->lhs)) );
479 SCIP_Bool* isupgraded /**< buffer to store whether the constraint has been upgraded (and deleted) */
511 if( consdata->z != NULL && !SCIPvarIsActive(consdata->z) && SCIPvarGetStatus(consdata->z) != SCIP_VARSTATUS_MULTAGGR )
556 * in the latter case, we just do nothing, which may not be most efficient, but should still work
675 /* mark that variables in constraint should not be multiaggregated (bad for bound tightening and branching) */
744 SCIP_CALL( SCIPgetProbvarLinearSum(scip, vars, coefs, &nvars, varssize, &constant, &requsize, TRUE) );
751 SCIP_CALL( SCIPgetProbvarLinearSum(scip, vars, coefs, &nvars, varssize, &constant, &requsize, TRUE) );
764 SCIP_CALL( SCIPexprgraphReplaceVarByLinearSum(conshdlrdata->exprgraph, var, nvars, coefs, (void**)vars, constant) );
838 /* project point onto box if from LP or very close to bounds to avoid eval error when function is not defined slightly outside bounds */
843 /* @todo handle case where variables are outside of bounds as in other constraint handlers, see also #627 */
870 SCIP_CALL( SCIPexprintEval(conshdlrdata->exprinterpreter, consdata->f, xyvals, &consdata->activity) );
917 SCIP_CONS** maxviolcon /**< buffer to store constraint with largest violation, or NULL if solution is feasible */
955 /** setup vred(s;x0,y0,ylb,yub) for a given f(x,y) for computing a convex-concave underestimator
956 * vred(s;x0,y0,ylb,yub) = (yub-y0)/(yub-ylb) f((yub-ylb)/(yub-y0)x0 - (y0-ylb)/(yub-y0)*s, ylb) + (y0-ylb)/(yub-ylb) f(s,yub)
980 assert(SCIPexprGetOperator(SCIPexprtreeGetRoot(f)) != SCIP_EXPR_VARIDX); /* substitute cannot substitute the root node, but f should not be a single variable anyway */
982 /* setup vred(s;x0,y0,ylb,yub) for computing a convex-concave underestimator in the case where y is not at one of its bounds
983 * vred(s;x0,y0,ylb,yub) = (yub-y0)/(yub-ylb) f((yub-ylb)/(yub-y0)x0 - (y0-ylb)/(yub-y0)*s, ylb) + (y0-ylb)/(yub-ylb) f(s,yub)
997 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &e5, SCIP_EXPR_DIV, e3, e4) ); /* x0(yub-ylb)/(yub-y0) */
1011 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &e6, SCIP_EXPR_DIV, e3, e4) ); /* s(y0-ylb)/(yub-y0) */
1040 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &e5, SCIP_EXPR_DIV, e3, e4) ); /* (yub-y0)/(yub-ylb) */
1045 SCIP_CALL( SCIPexprCreateLinear(SCIPblkmem(scip), &e6, 1, &e1, &minusone, 1.0) ); /* 1 - (yub-y0)/(yub-ylb) */
1105 /* setup f(x,yfixed) for computing a convex-concave underestimator in the case where y is at one of its bounds */
1106 SCIP_CALL( SCIPexprtreeCopy(SCIPblkmem(scip), &consdata->sepaconvexconcave.f_yfixed, consdata->f) );
1127 /* setup vred(s;x0,y0,ylb,yub) for computing a convex-concave underestimator in the case where y is not at one of its bounds
1128 * vred(s;x0,y0,ylb,yub) = (yub-y0)/(yub-ylb) f((yub-ylb)/(yub-y0)x0 - (y0-ylb)/(yub-y0)*s, ylb) + (y0-ylb)/(yub-ylb) f(s,yub)
1163 SCIP_CALL( SCIPexprtreeCreate(SCIPblkmem(scip), &consdata->sepaconvexconcave.f_neg_swapped, minusf, 2, 0, NULL) );
1171 /* setup -f(y, xfixed) for computing a convex-concave overestimator in the case where x is at on of it's bounds */
1172 SCIP_CALL( SCIPexprtreeCopy(SCIPblkmem(scip), &consdata->sepaconvexconcave.f_neg_swapped_yfixed, consdata->sepaconvexconcave.f_neg_swapped) );
1181 SCIP_CALL( SCIPexprtreeSubstituteVars(consdata->sepaconvexconcave.f_neg_swapped_yfixed, subst) );
1191 SCIP_CALL( SCIPexprintCompile(exprinterpreter, consdata->sepaconvexconcave.f_neg_swapped_yfixed) );
1193 /* setup vred(s;y0,x0,xlb,xub) for computing a convex-concave underestimator in the case where x is not at one of its bounds */
1194 SCIP_CALL( initSepaDataCreateVred(scip, &consdata->sepaconvexconcave.vred_neg_swapped, consdata->sepaconvexconcave.f_neg_swapped) );
1195 SCIP_CALL( SCIPexprintCompile(exprinterpreter, consdata->sepaconvexconcave.vred_neg_swapped) );
1285 /** solves an equation f'(s) = constant for a univariate convex or concave function f with respect to bounds on s
1286 * if there is no s between the bounds such that f'(s) = constant, then it returns the closest bound (and still claims success)
1358 /* SCIPdebugMsg(scip, "s = %.15g [%g,%g] f(s) = %g grad = %g (perturbed by %g)\n", s, lb, ub, fval, grad, iter <= 65 ? 0.1 / (1<<iter) : 1e-20); */
1381 /* if f cannot be two times differentiated at s, take the Hessian from another point close by */
1394 * (multiply instead of divide by hess for the case that hess is zero and since only the sign matters
1417 /* if grad is targetvalue (w.r.t. feastol) and step length would be almost 0, then we are also done */
1446 /** generates a cut for f(x,y) + c*z <= rhs with f(x,y) being convex or 1-convex with x or y fixed or convex-concave with y fixed
1455 SCIP_Bool newxy, /**< whether the last evaluation of f(x,y) with the expression interpreter was at (x0, y0) */
1486 (consdata->convextype == SCIP_BIVAR_1CONVEX_INDEFINITE && (SCIPisEQ(scip, SCIPvarGetLbLocal(x), SCIPvarGetUbLocal(x)) || SCIPisEQ(scip, SCIPvarGetLbLocal(y), SCIPvarGetUbLocal(y)))) ||
1487 (consdata->convextype == SCIP_BIVAR_CONVEX_CONCAVE && SCIPisEQ(scip, SCIPvarGetLbLocal(y), SCIPvarGetUbLocal(y))) );
1510 (void) SCIPsnprintf(rowname, SCIP_MAXSTRLEN, "%s_linearization_%d", SCIPconsGetName(cons), SCIPgetNLPs(scip));
1512 SCIP_CALL( SCIPcreateEmptyRowCons(scip, row, SCIPconsGetHdlr(cons), rowname, -SCIPinfinity(scip), rhs, FALSE, FALSE /* modifiable */, TRUE /* removable */) );
1522 /** given a convex (concave, resp.) bivariate function, computes an over- (under-, resp.) estimating hyperplane
1530 SCIP_Bool doover, /**< whether to compute an overestimator (TRUE) or an underestimator (FALSE) */
1535 SCIP_Bool* success /**< pointer to indicate whether coefficients where successfully computed */
1586 if( SCIPisInfinity(scip, -xlb) || SCIPisInfinity(scip, xub) || SCIPisInfinity(scip, -ylb) || SCIPisInfinity(scip, yub) )
1588 SCIPdebugMsg(scip, "skip estimating hyperplane since <%s> or <%s> is unbounded\n", SCIPvarGetName(x), SCIPvarGetName(y));
1594 SCIPdebugMsg(scip, "skip estimating hyperplane since both <%s> and <%s> are fixed\n", SCIPvarGetName(x), SCIPvarGetName(y));
1622 if( !SCIPisFinite(p1val) || SCIPisInfinity(scip, REALABS(p1val)) || !SCIPisFinite(p4val) || SCIPisInfinity(scip, REALABS(p4val)) )
1645 if( !SCIPisFinite(p1val) || SCIPisInfinity(scip, REALABS(p1val)) || !SCIPisFinite(p2val) || SCIPisInfinity(scip, REALABS(p2val)) )
1665 /* if we want an underestimator, flip f(x,y), i.e., do as if we compute an overestimator for -f(x,y) */
1679 if( !SCIPisFinite(p1val) || SCIPisInfinity(scip, REALABS(p1val)) || !SCIPisFinite(p2val) || SCIPisInfinity(scip, REALABS(p2val)) ||
1680 ! SCIPisFinite(p3val) || SCIPisInfinity(scip, REALABS(p3val)) || !SCIPisFinite(p4val) || SCIPisInfinity(scip, REALABS(p4val)) )
1690 * Since we assume that f is convex, we then know that all points (x,y,f(x,y)) are below this hyperplane, i.e.,
1699 SCIP_CALL( SCIPcomputeHyperplaneThreePoints(scip, p1[0], p1[1], p1val, p2[0], p2[1], p2val, p3[0], p3[1], p3val, &alpha,
1702 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p1[0] + beta * p1[1] + gamma_ * p1val, delta));
1703 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p2[0] + beta * p2[1] + gamma_ * p2val, delta));
1704 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p3[0] + beta * p3[1] + gamma_ * p3val, delta));
1706 /* if hyperplane through p1,p2,p3 does not overestimate f(p4), then it must be the other variant */
1712 SCIP_CALL( SCIPcomputeHyperplaneThreePoints(scip, p1[0], p1[1], p1val, p3[0], p3[1], p3val, p4[0], p4[1], p4val, &alpha,
1715 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p1[0] + beta * p1[1] + gamma_ * p1val, delta));
1716 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p3[0] + beta * p3[1] + gamma_ * p3val, delta));
1717 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p4[0] + beta * p4[1] + gamma_ * p4val, delta));
1719 /* if hyperplane through p1,p3,p4 does not overestimate f(p2), then it must be the other variant */
1728 SCIP_CALL( SCIPcomputeHyperplaneThreePoints(scip, p1[0], p1[1], p1val, p2[0], p2[1], p2val, p4[0], p4[1], p4val,
1732 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p1[0] + beta * p1[1] + gamma_ * p1val, delta));
1733 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p2[0] + beta * p2[1] + gamma_ * p2val, delta));
1734 assert(SCIPisInfinity(scip, delta) || SCIPisFeasLE(scip, alpha * p3[0] + beta * p3[1] + gamma_ * p3val, delta));
1735 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p4[0] + beta * p4[1] + gamma_ * p4val, delta));
1739 SCIP_CALL( SCIPcomputeHyperplaneThreePoints(scip, p2[0], p2[1], p2val, p3[0], p3[1], p3val, p4[0], p4[1], p4val,
1743 assert(SCIPisInfinity(scip, delta) || SCIPisFeasLE(scip, alpha * p1[0] + beta * p1[1] + gamma_ * p1val, delta));
1744 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p2[0] + beta * p2[1] + gamma_ * p2val, delta));
1745 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p3[0] + beta * p3[1] + gamma_ * p3val, delta));
1746 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p4[0] + beta * p4[1] + gamma_ * p4val, delta));
1750 SCIPdebugMsg(scip, "alpha = %g, beta = %g, gamma = %g, delta = %g\n", alpha, beta, gamma_, delta);
1794 SCIP_CALL( generateEstimatingHyperplane(scip, exprinterpreter, consdata->f, TRUE, x0y0, &coefs[0], &coefs[1], &constant, &success) );
1803 SCIP_CALL( SCIPcreateRowCons(scip, row, SCIPconsGetHdlr(cons), "bivaroveresthyperplanecut", 0, NULL, NULL, consdata->lhs - constant, SCIPinfinity(scip), TRUE, FALSE, TRUE) );
1811 SCIPdebugMsg(scip, "failed to compute overestimator for all-convex constraint <%s>\n", SCIPconsGetName(cons));
1903 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e1, SCIPexprtreeGetRoot(f)) ); /* e1 = f(x,y) */
1906 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp2, SCIP_EXPR_CONST, 1.0 - 1.0 / t) ); /* tmp2 = 1-1/t */
1907 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp, SCIP_EXPR_MUL, tmp, tmp2) ); /* tmp = (1-1/t)*s */
1910 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp2, SCIP_EXPR_CONST, 1/t*xval) ); /* tmp2 = 1/t*xval */
1911 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp, SCIP_EXPR_PLUS, tmp, tmp2) ); /* tmp = 1/t*xval + (1-1/t)*s */
1915 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[1], SCIP_EXPR_CONST, ylb) ); /* tmp = ylb */
1917 assert(SCIPexprGetOperator(e1) != SCIP_EXPR_VARIDX); /* substitute cannot substitute the root node, but f should not be a single variable anyway */
1918 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e1, subst) ); /* e1 = f(1/t*xval + (1-1/t)*s, ylb) */
1924 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e2, SCIPexprtreeGetRoot(f)) ); /* e2 = f(x,y) */
1930 assert(SCIPexprGetOperator(e2) != SCIP_EXPR_VARIDX); /* substitute cannot substitute the root node, but f should not be a single variable anyway */
1937 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &e1, SCIP_EXPR_MUL, e1, tmp) ); /* e1 = t * f(1/t*xval+(1-1/t)*s,ylb) */
1939 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp, SCIP_EXPR_CONST, 1.0 - t) ); /* tmp = 1 - t */
1940 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &e2, SCIP_EXPR_MUL, e2, tmp) ); /* e2 = (1-t) * f(s, yub) */
1957 SCIP_CALL( solveDerivativeEquation(scip, exprinterpreter, vredtree, 0.0, slb, sub, &sval, success) );
2025 SCIPdebugMsg(scip, "Parallel: r=%g in [%g,%g], s=%g in [%g,%g], f(r,ylb)=%g, f(xlb,s)=%g\n",rval,xlb,xub,sval,ylb,yub,frval,fsval);
2026 SCIPdebugMsg(scip, "(r,ylb)=(%g,%g), (s,yub)=(%g,%g), vredval=%g\n",rval,ylb,sval,yub,*convenvvalue);
2040 SCIPdebugMsg(scip, "Parallel: cutcoeff[0]=%g, cutcoeff[1]=%g, cutcoeff[2]=1.0, cutcoeff[3]=%g\n",cutcoeff[0]/cutcoeff[2],cutcoeff[1]/cutcoeff[2],cutcoeff[3]/cutcoeff[2]);
2130 SCIPdebugMsg(scip, "%s[%g,%g] = %g %s[%g,%g] = %g\n", SCIPvarGetName(x), xlb, xub, xval, SCIPvarGetName(y), ylb, yub, yval);
2140 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp, SCIP_EXPR_CONST, yval-ylb) ); /* tmp = yval-ylb */
2141 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_DIV, tmp, expr) ); /* expr = (yval-ylb) / t */
2145 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_PLUS, expr, tmp) ); /* expr = ylb + (yval-ylb) / t */
2149 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[0], SCIP_EXPR_CONST, xlb) ); /* subst[0] = xlb */
2151 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e1, SCIPexprtreeGetRoot(f)) ); /* e1 = f(x,y) */
2152 assert(SCIPexprGetOperator(e1) != SCIP_EXPR_VARIDX); /* expr substitute vars cannot substitute the root node, but f should not be a single variable anyway */
2153 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e1, subst) ); /* e1 = f(xlb, ylb + (yval-ylb)/t) */
2161 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr1, SCIP_EXPR_MINUS, tmp, expr1) ); /* expr1 = 1-t */
2165 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MUL, expr2, tmp) ); /* expr2 = xlb * t */
2167 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MINUS, tmp, expr2) ); /* expr2 = xval - xlb * t */
2169 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_DIV, expr2, expr1) ); /* expr = (xval-t*xlb)/(1-t) */
2172 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[1], SCIP_EXPR_CONST, ylb) ); /* subst[0] = ylb */
2174 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e2, SCIPexprtreeGetRoot(f)) ); /* e2 = f(x,y) */
2175 assert(SCIPexprGetOperator(e2) != SCIP_EXPR_VARIDX); /* expr substitute vars cannot substitute the root node, but f should not be a single variable anyway */
2176 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e2, subst) ); /* e2 = f((xval-xlb*t)/(1-t), ylb) */
2184 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr1, SCIP_EXPR_MUL, expr, e1) ); /* expr1 = t * e1*/
2188 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_MINUS, tmp, expr) ); /* expr = 1 - t */
2189 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MUL, expr, e2) ); /* expr2 = (1-t) * e2 */
2200 SCIP_CALL( solveDerivativeEquation(scip, exprinterpreter, vredtree, 0.0, tlb, tub, &tval, success) );
2266 if( !SCIPisFinite(grad_sval[0]) || !SCIPisFinite(grad_rval[0]) || SCIPisInfinity(scip, REALABS(MIN(grad_sval[0],grad_rval[0]))) )
2268 /* FIXME maybe it is sufficient to have one of them finite, using that one for the MIN below? */
2279 SCIPdebugMsg(scip, "LowerLeft: r=%g in [%g,%g], s=%g in [%g,%g], f(s,ylb)=%g, f(xlb,r)=%g\n",rval,xlb,xub,sval,ylb,yub,fsval,frval);
2280 SCIPdebugMsg(scip, "(s,ylb)=(%g,%g) (xlb,r)=(%g,%g) t=%g, vredval=%g\n",sval,ylb,xlb,rval,tval,*convenvvalue);
2281 SCIPdebugMsg(scip, "LowerLeft: cutcoeff[0]=%g, cutcoeff[1]=%g,cutcoeff[2]=%g,cutcoeff[3]=%g\n",cutcoeff[0],cutcoeff[1],cutcoeff[2],cutcoeff[3]);
2290 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp, SCIP_EXPR_CONST, yval-yub) ); /* tmp = yval-yub*/
2291 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_DIV, tmp, expr) ); /* expr = (yval-yub) / t */
2295 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_PLUS, expr, tmp) ); /* expr = yub + (yval-yub)/t */
2299 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[0], SCIP_EXPR_CONST, xub) ); /* tmp = xub */
2301 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e1, SCIPexprtreeGetRoot(f)) ); /* e1 = f(x,y) */
2303 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e1, subst) ); /* e1 = f(xub, yub + (yval-yub)/t) */
2311 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr1, SCIP_EXPR_MINUS, tmp, expr1) ); /* expr1 = 1-t */
2315 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MUL, expr2, tmp) ); /* expr2 = xub * t */
2317 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MINUS, tmp, expr2) ); /* expr2 = xval - xub * t */
2319 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_DIV, expr2, expr1) ); /* expr = (xval-t*xub)/(1-t) */
2322 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[1], SCIP_EXPR_CONST, yub) ); /* tmp = yub */
2324 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e2, SCIPexprtreeGetRoot(f)) ); /* e2 = f(x,y) */
2326 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e2, subst) ); /* e2 = f((xval-t*xub)/(1-t), yub) */
2333 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr1, SCIP_EXPR_MUL, e1, expr) ); /* expr1 = t * e1*/
2337 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_MINUS, tmp, expr) ); /* expr = 1-t */
2339 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MUL, e2, expr) ); /* expr2 = (1-t) * e2*/
2350 SCIP_CALL( solveDerivativeEquation(scip, exprinterpreter, vredtree, 0.0, tlb, tub, &tval, success) );
2422 if( !SCIPisFinite(grad_sval[0]) || !SCIPisFinite(grad_rval[0]) || SCIPisInfinity(scip, REALABS(MIN(grad_sval[0],grad_rval[0]))) )
2424 /* FIXME maybe it is sufficient to have one of them finite, using that one for the MIN below? */
2436 SCIPdebugMsg(scip, "UpperRight: r=%g in [%g,%g], s=%g in [%g,%g], f(r,yub)=%g, f(xub,s)=%g\n",rval,xlb,xub,sval,ylb,yub,frval,fsval);
2437 SCIPdebugMsg(scip, "(s,yub)=(%g,%g) (xub,r)=(%g,%g) t=%g, vredval=%g\n",sval,yub,xub,rval,tval,*convenvvalue);
2438 SCIPdebugMsg(scip, "UpperRight: cutcoeff[0]=%g, cutcoeff[1]=%g, cutcoeff[2]=%g, cutcoeff[3]=%g\n",cutcoeff[0],cutcoeff[1],cutcoeff[2],cutcoeff[3]);
2534 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp, SCIP_EXPR_CONST, xval-xub) ); /* tmp = xval-xub */
2535 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_DIV, tmp, expr) ); /* expr = (xval-xub)/t */
2539 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_PLUS, expr, tmp) ); /* expr = xub + (xval-xub)/t */
2543 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[1], SCIP_EXPR_CONST, ylb) ); /* subst[1] = ylb */
2545 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e1, SCIPexprtreeGetRoot(f)) ); /* e1 = f(x,y) */
2547 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e1, subst) ); /* e1 = f(xub + (xval-xub)/t, ylb) */
2555 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr1, SCIP_EXPR_MINUS, tmp, expr1) ); /* expr1 = 1-t */
2559 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MUL, expr2, tmp) ); /* expr2 = ylb * t */
2561 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MINUS, tmp, expr2) ); /* expr2 = yval - ylb * t */
2564 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_DIV, expr2, expr1) ); /* expr = (yval-t*ylb)/(1-t) */
2567 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[0], SCIP_EXPR_CONST, xub) ); /* subst[0] = xub */
2569 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e2, SCIPexprtreeGetRoot(f)) ); /* e2 = f(x,y) */
2571 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e2, subst) ); /* e2 = f(xub, (yval-t*ylb)/(1-t)) */
2578 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr1, SCIP_EXPR_MUL, e1, expr) ); /* expr1 = t * e1*/
2582 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_MINUS, tmp, expr) ); /* expr = 1-t */
2583 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MUL, e2, expr) ); /* expr2 = (1-t) * e2*/
2594 SCIP_CALL( solveDerivativeEquation(scip, exprinterpreter, vredtree, 0.0, tlb, tub, &tval, success) );
2657 if( !SCIPisFinite(grad_sval[0]) || !SCIPisFinite(grad_rval[0]) || SCIPisInfinity(scip, REALABS(MIN(grad_sval[0],grad_rval[0]))) )
2659 /* FIXME maybe it is sufficient to have one of them finite, using that one for the MIN below? */
2670 SCIPdebugMsg(scip, "LowerRight: t=%g in [%g,%g], r=%g in [%g,%g], s=%g in [%g,%g]\n",tval,tlb,tub,rval,xlb,xub,sval,ylb,yub);
2671 SCIPdebugMsg(scip, "LowerRight: (r,ylb)=(%g,%g) (xub,sval)=(%g,%g) vredval=%g\n",rval,ylb,xub,sval,*convenvvalue);
2672 SCIPdebugMsg(scip, "LowerRight: cutcoeff[0]=%g, cutcoeff[1]=%g,cutcoeff[2]=1.0,cutcoeff[3]=%g\n",cutcoeff[0]/cutcoeff[2],cutcoeff[1]/cutcoeff[2],cutcoeff[3]/cutcoeff[2]);
2681 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp, SCIP_EXPR_CONST, xval-xlb) ); /* tmp = xval-xlb */
2682 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_DIV, tmp, expr) ); /* expr = (xval-xlb)/lambda */
2686 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_PLUS, expr, tmp) ); /* expr = xlb + (xval-xlb)/t */
2690 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[1], SCIP_EXPR_CONST, yub) ); /* subst[1] = yub */
2692 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e1, SCIPexprtreeGetRoot(f)) ); /* e1 = f(x,y) */
2694 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e1, subst) ); /* e1 = f(xlb + (xval-xlb)/t, yub) */
2702 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr1, SCIP_EXPR_MINUS, tmp, expr1) ); /* expr1 = 1-t */
2706 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MUL, expr2, tmp) ); /* expr2 = yub * t */
2708 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MINUS, tmp, expr2) ); /* expr2 = yval - yub * t */
2711 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_DIV, expr2, expr1) ); /* expr = (yval-t*yub)/(1-t) */
2714 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[0], SCIP_EXPR_CONST, xlb) ); /* subst[0] = xlb */
2716 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e2, SCIPexprtreeGetRoot(f)) ); /* e2 = f(x,y) */
2717 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e2, subst) ); /* e2 = f( xlb , (yval-t*yub)/(1-t) ) */
2724 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr1, SCIP_EXPR_MUL, e1, expr) ); /* expr1 = t * e1*/
2728 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_MINUS, tmp, expr) ); /* expr = 1-t */
2729 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MUL, e2, expr) ); /* expr2 = (1-t) * e2*/
2740 SCIP_CALL( solveDerivativeEquation(scip, exprinterpreter, vredtree, 0.0, tlb, tub, &tval, success) );
2803 if( !SCIPisFinite(grad_sval[0]) || !SCIPisFinite(grad_rval[0]) || SCIPisInfinity(scip, REALABS(MIN(grad_rval[0],grad_sval[0]))) )
2805 /* FIXME maybe it is sufficient to have one of them finite, using that one for the MIN below? */
2816 SCIPdebugMsg(scip, "UpperLeft: r=%g in [%g,%g], s=%g in [%g,%g], f(r,yub)=%g, f(xlb,s)=%g\n",rval,xlb,xub,sval,ylb,yub,frval,fsval);
2817 SCIPdebugMsg(scip, "t=%g in [%g,%g], (r,yub)=(%g,%g) (xlb,sval)=(%g,%g) vredval=%g\n",tval,tlb,tub,rval,yub,xlb,sval,*convenvvalue);
2818 SCIPdebugMsg(scip, "UpperLeft: cutcoeff[0]=%g, cutcoeff[1]=%g,cutcoeff[2]=1.0,cutcoeff[3]=%g\n",cutcoeff[0]/cutcoeff[2],cutcoeff[1]/cutcoeff[2],cutcoeff[3]/cutcoeff[2]);
2825 /** generates a linear underestimator for f(x,y) with f(x,y) being STRICTLY convex in x and concave in y
2826 * generate coefficients cutcoeff = (alpha, beta, gamma, delta), such that alpha * x + beta * y - delta <= gamma * f(x,y)
2955 SCIPdebugMsg(scip, "cannot evaluate function or derivative in (xval,ylb), also after perturbation\n");
2993 if( !SCIPisFinite(gradylb[0]) || !SCIPisFinite(gradyub[0]) || !SCIPisFinite(fvalylb) || !SCIPisFinite(fvalyub) ||
3050 SCIPdebug( SCIP_CALL( SCIPexprtreePrintWithNames(f_yfixed, SCIPgetMessagehdlr(scip), NULL) ) );
3056 SCIP_CALL( solveDerivativeEquation(scip, exprinterpreter, f_yfixed, grad[0], xlb, xub, &xtilde, success) );
3063 /* if we could not find an xtilde such that f'(xtilde,yub) = f'(xval,ylb), then probably because f'(x,yub) is constant
3064 * in this case, choose xtilde from {xlb, xub} such that it maximizes f'(xtilde, yub) - grad[0]*xtilde
3071 SCIPdebugMsg(scip, "couldn't solve deriv equ, compare f(%g,%g) - %g*%g = %g and f(%g,%g) - %g*%g = %g\n",
3105 SCIPdebugMsg(scip, "alpha: %g, beta: %g, gamma: %g, delta: %g\n", cutcoeff[0], cutcoeff[1], cutcoeff[2], cutcoeff[3]);
3142 SCIP_CALL( solveDerivativeEquation(scip, exprinterpreter, f_yfixed, grad[0], xlb, xub, &xtilde, success) );
3149 /* if we could not find an xtilde such that f'(xtilde,ylb) = f'(xval,yub), then probably because f'(x,ylb) is constant
3150 * in this case, choose xtilde from {xlb, xub} such that it maximizes f'(xtilde, yub) - grad[0]*xtilde
3157 SCIPdebugMsg(scip, "couldn't solve deriv equ, compare f(%g,%g) - %g*%g = %g and f(%g,%g) - %g*%g = %g\n",
3191 SCIPdebugMsg(scip, "alpha: %g, beta: %g, gamma: %g, delta: %g\n", cutcoeff[0], cutcoeff[1], cutcoeff[2], cutcoeff[3]);
3253 SCIP_CALL( solveDerivativeEquation(scip, exprinterpreter, vred, 0.0, slb, sub, &sval, success) );
3316 SCIPdebugMsg(scip, "Parallel: r=%g s=%g in [%g,%g], y in [%g,%g], f(r,ylb)=%g, f(xlb,s)=%g\n",rval,sval,xlb,xub,ylb,yub,frval,fsval);
3317 SCIPdebugMsg(scip, "(r,ylb)=(%g,%g), (s,yub)=(%g,%g), vredval=%g\n",rval,ylb,sval,yub,*convenvvalue);
3332 SCIPdebugMsg(scip, "Parallel: cutcoeff[0]=%g, cutcoeff[1]=%g,cutcoeff[2]=1.0,cutcoeff[3]=%g\n",cutcoeff[0]/cutcoeff[2],cutcoeff[1]/cutcoeff[2],cutcoeff[3]/cutcoeff[2]);
3340 /** generates a cut for one side of lhs <= f(x,y) + c*z <= rhs with f(x,y) being convex in x and concave in y */
3384 SCIP_CALL( generateEstimatingHyperplane(scip, exprinterpreter, consdata->f, TRUE, xyref, &coefs[0], &coefs[1], &constant, &success) );
3392 (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "%s_overesthyperplanecut_%d", SCIPconsGetName(cons), SCIPgetNLPs(scip));
3393 SCIP_CALL( SCIPcreateRowCons(scip, row, SCIPconsGetHdlr(cons), cutname, 0, NULL, NULL, consdata->lhs - constant, SCIPinfinity(scip), TRUE, FALSE, TRUE) );
3406 /* f is strictly concave in y -> can compute overestimator by applying generateConvexConcaveUnderstimator on -f(y,x) */
3411 SCIP_CALL( generateConvexConcaveUnderestimator(scip, exprinterpreter, consdata->sepaconvexconcave.f_neg_swapped, consdata->sepaconvexconcave.f_neg_swapped_yfixed, consdata->sepaconvexconcave.vred_neg_swapped, xyref_, cutcoeff, &dummy, &success) );
3428 (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "%s_convexconcaveoverest_%d", SCIPconsGetName(cons), SCIPgetNLPs(scip));
3429 SCIP_CALL( SCIPcreateEmptyRowCons(scip, row, SCIPconsGetHdlr(cons), cutname, consdata->lhs - cutcoeff[3]/cutcoeff[2], SCIPinfinity(scip),
3450 SCIP_CALL( generateEstimatingHyperplane(scip, exprinterpreter, consdata->f, FALSE, xyref, &coefs[0], &coefs[1], &constant, &success) );
3458 (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "%s_underesthyperplanecut_%d", SCIPconsGetName(cons), SCIPgetNLPs(scip));
3459 SCIP_CALL( SCIPcreateRowCons(scip, row, SCIPconsGetHdlr(cons), cutname, 0, NULL, NULL, -SCIPinfinity(scip), consdata->rhs - constant, TRUE, FALSE, TRUE) );
3470 /* f is strictly convex in x -> can compute underestimator by applying generateConvexConcaveUnderstimator */
3471 assert(!consdata->sepaconvexconcave.linearinx); /* generateConvexConcaveUnderestimator assumes that if f is strictly convex in x */
3473 SCIP_CALL( generateConvexConcaveUnderestimator(scip, exprinterpreter, consdata->f, consdata->sepaconvexconcave.f_yfixed, consdata->sepaconvexconcave.vred, xyref, cutcoeff, &dummy, &success) );
3491 (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "%s_convexconcaveunderest_%d", SCIPconsGetName(cons), SCIPgetNLPs(scip));
3492 SCIP_CALL( SCIPcreateEmptyRowCons(scip, row, SCIPconsGetHdlr(cons), cutname, -SCIPinfinity(scip), consdata->rhs + cutcoeff[3]/cutcoeff[2],
3507 /** computes an underestimating hyperplane for functions that are convex in x and y if the point to cut off lies on the boundary */
3595 /** generate a linear underestimator for f(x,y) with f(x,y) being convex in x and convex in y and the point to cut off lies on the boundary
3596 * generate coefficients cutcoeff = (alpha, beta, gamma, delta), such that alpha * x + beta * y - delta <= gamma * f(x,y)
3704 SCIP_CALL( lifting(scip,exprinterpreter,f,xval,yval,xlb,xlb,ylb,yub,-1,cutcoeff,convenvvalue,success) );
3721 SCIP_CALL( lifting(scip,exprinterpreter,f,xval,yval,xlb,xub,ylb,ylb,-1,cutcoeff,convenvvalue,success) );
3746 SCIP_CALL( lifting(scip,exprinterpreter,f,xval,yval,xub,xub,ylb,yub,1,cutcoeff,convenvvalue,success) );
3763 SCIP_CALL( lifting(scip,exprinterpreter,f,xval,yval,xlb,xub,yub,yub,1,cutcoeff,convenvvalue,success) );
3777 SCIPerrorMessage("Tries to compute underestimator for a point at the boundary. But point is not on the boundary!\n");
3781 /** generates a linear underestimator for f(x,y) with f(x,y) being convex in x and convex in y but indefinite
3782 * This is for the case where the cone of the concave directions is (R_+ x R_-) union (R_\- x R_+).
3855 if( !SCIPisFinite(fval_xub_ylb) || SCIPisInfinity(scip, REALABS(fval_xub_ylb)) || !SCIPisFinite(fval_xlb_yub) || SCIPisInfinity(scip, REALABS(fval_xlb_yub)) )
3871 SCIPdebugMsg(scip, "xval=%g in [%g,%g], yval=%g in [%g,%g]\n", xyref[0], xlb, xub, xyref[1], ylb, yub);
3902 SCIP_CALL( generateOrthogonal_lx_ly_Underestimator(scip, exprinterpreter, f, xyref, all_cutcoeff[0], &all_convenvvalue[0], &all_success[0]) );
3904 SCIP_CALL( generateUnderestimatorParallelYFacets(scip, exprinterpreter, f, xyref, all_cutcoeff[1], &all_convenvvalue[1], &all_success[1]) );
3916 SCIP_CALL( generateOrthogonal_lx_ly_Underestimator(scip, exprinterpreter, fswapped, xyref_, all_cutcoeff[0], &all_convenvvalue[0], &all_success[0]) ); /*lint !e644*/
3918 SCIP_CALL( generateUnderestimatorParallelYFacets(scip, exprinterpreter, fswapped, xyref_, all_cutcoeff[1], &all_convenvvalue[1], &all_success[1]) );
3975 /** generates a linear underestimator for f(x,y) with f(x,y) being convex in x and convex in y but indefinite
3976 * This is for the case where the cone of the concave directions is (R_+ x R_+) union (R_- x R_-).
3985 * Generates coefficients cutcoeff = (alpha, beta, gamma, delta), such that alpha * x + beta * y - delta <= gamma * f(x,y)
4054 if( !SCIPisFinite(fval_xlb_ylb) || SCIPisInfinity(scip, REALABS(fval_xlb_ylb)) || !SCIPisFinite(fval_xub_yub) || SCIPisInfinity(scip, REALABS(fval_xub_yub)) )
4066 SCIPdebugMsg(scip, "xval=%g in [%g,%g], yval=%g in [%g,%g]\n",xyref[0],xlb,xub,xyref[1],ylb,yub);
4069 if( SCIPisGE( scip, fval_xlb_ylb+(yub-ylb)*grad_xlb_ylb[1], fval_xub_yub+(xlb-xub)*grad_xub_yub[0] ) )
4096 SCIP_CALL( generateOrthogonal_lx_uy_Underestimator(scip, exprinterpreter, f, xyref, all_cutcoeff[0], &all_convenvvalue[0], &all_success[0]) );
4098 SCIP_CALL( generateUnderestimatorParallelYFacets(scip, exprinterpreter, f, xyref, all_cutcoeff[1], &all_convenvvalue[1], &all_success[1]) );
4109 SCIP_CALL( generateOrthogonal_lx_uy_Underestimator(scip, exprinterpreter, fswapped, xyref_, all_cutcoeff[0], &all_convenvvalue[0], &all_success[0]) ); /*lint !e644*/
4111 SCIP_CALL( generateUnderestimatorParallelYFacets(scip, exprinterpreter, fswapped, xyref_, all_cutcoeff[1], &all_convenvvalue[1], &all_success[1]) );
4168 /** generates a linear underestimator for f(x,y) with f(x,y) being convex in x and convex in y but indefinite
4169 * generate coefficients cutcoeff = (alpha, beta, gamma, delta), such that alpha * x + beta * y - delta <= gamma * f(x,y)
4226 if( SCIPisInfinity(scip, -xlb) || SCIPisInfinity(scip, xub) || SCIPisInfinity(scip, -ylb) || SCIPisInfinity(scip, yub) )
4228 SCIPdebugMsg(scip, "skip underestimate for 1-convex indefinite constraint <%s> since <%s> or <%s> is unbounded\n", SCIPconsGetName(cons), SCIPvarGetName(x), SCIPvarGetName(y));
4239 if( SCIPisFeasEQ(scip,xyref[0],xlb) || SCIPisFeasEQ(scip,xyref[0],xub) || SCIPisFeasEQ(scip,xyref[1],ylb) || SCIPisFeasEQ(scip,xyref[1],yub) )
4241 SCIP_CALL( generate1ConvexIndefiniteUnderestimatorAtBoundary(scip, exprinterpreter, f, xyref, cutcoeff, &convenvvalue, &success) );
4264 SCIP_CALL( generate1ConvexIndefiniteUnderestimatorInTheInteriorPatternA(scip, exprinterpreter, f, xyref, cutcoeff, &convenvvalue, &success) );
4270 SCIP_CALL( generate1ConvexIndefiniteUnderestimatorInTheInteriorPatternB(scip, exprinterpreter, f, xyref, cutcoeff, &convenvvalue, &success) );
4306 SCIP_CALL( SCIPcreateEmptyRowCons(scip, row, SCIPconsGetHdlr(cons), "1ConvexUnderest", -SCIPinfinity(scip), rhs,
4308 SCIP_CALL( SCIPaddVarToRow(scip, *row, SCIPexprtreeGetVars(consdata->f)[0], cutcoeff[0] / cutcoeff[2]) );
4309 SCIP_CALL( SCIPaddVarToRow(scip, *row, SCIPexprtreeGetVars(consdata->f)[1], cutcoeff[1] / cutcoeff[2]) );
4360 SCIPdebugMsg(scip, "generate cut for constraint <%s> with %s hand side violated by %g\n", SCIPconsGetName(cons), violside == SCIP_SIDETYPE_LEFT ? "left" : "right", violside == SCIP_SIDETYPE_LEFT ? consdata->lhsviol : consdata->rhsviol);
4366 SCIPdebugMsgPrint(scip, ", %s = %g with bounds [%g, %g]", SCIPvarGetName(consdata->z), SCIPgetSolVal(scip, sol, consdata->z), SCIPvarGetLbLocal(consdata->z), SCIPvarGetUbLocal(consdata->z));
4436 SCIPdebugMsg(scip, "cut coefficients for constraint <%s> have very large range: mincoef = %g maxcoef = %g\n", SCIPconsGetName(cons), mincoef, maxcoef);
4438 /* if minimal coefficient is given by z, then give up (probably the maximal coefficient is the problem) */
4441 SCIPdebugMsg(scip, "could not eliminate small coefficient, since it comes from linear part\n");
4456 if( ((coef > 0.0 && violside == SCIP_SIDETYPE_RIGHT) || (coef < 0.0 && violside == SCIP_SIDETYPE_LEFT)) && !SCIPisInfinity(scip, -SCIPvarGetLbLocal(var)) )
4458 SCIPdebugMsg(scip, "eliminate coefficient %g for <%s> = %g [%g, %g]\n", coef, SCIPvarGetName(var), SCIPgetSolVal(scip, sol, var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var));
4465 if( ((coef < 0.0 && violside == SCIP_SIDETYPE_RIGHT) || (coef > 0.0 && violside == SCIP_SIDETYPE_LEFT)) && !SCIPisInfinity(scip, SCIPvarGetUbLocal(var)) )
4467 SCIPdebugMsg(scip, "eliminate coefficient %g for <%s> = %g [%g, %g]\n", coef, SCIPvarGetName(var), SCIPgetSolVal(scip, sol, var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var));
4501 SCIPdebugMsg(scip, "drop row for constraint <%s> because range of coefficients is too large: mincoef = %g, maxcoef = %g -> range = %g\n",
4509 SCIPdebugMsg(scip, "drop row for constraint <%s> because of very large side: %g\n", SCIPconsGetName(cons), violside == SCIP_SIDETYPE_LEFT ? -SCIProwGetLhs(*row) : SCIProwGetRhs(*row));
4518 * i.e., if side == RIGHT, then returns whether constraint function is convex w.r.t. local bounds
4562 return (side == SCIP_SIDETYPE_RIGHT && SCIPisEQ(scip, SCIPvarGetLbLocal(xy[1]), SCIPvarGetUbLocal(xy[1]))) ||
4563 (side == SCIP_SIDETYPE_LEFT && SCIPisEQ(scip, SCIPvarGetLbLocal(xy[0]), SCIPvarGetUbLocal(xy[0])));
4596 SCIPinfoMessage(scip, NULL, "splot [%g:%g] [%g:%g] ", SCIPvarGetLbLocal(x), SCIPvarGetUbLocal(x), SCIPvarGetLbLocal(y), SCIPvarGetUbLocal(y));
4598 SCIPinfoMessage(scip, NULL, "%+g", side == SCIP_SIDETYPE_LEFT ? consdata->lhs : consdata->rhs);
4600 SCIPinfoMessage(scip, NULL, ", %g", SCIPisInfinity(scip, SCIProwGetRhs(row)) ? -SCIProwGetLhs(row) : -SCIProwGetRhs(row));
4612 SCIPinfoMessage(scip, NULL, ", \"< echo '%g %g %g'\" with circles", SCIPgetSolVal(scip, sol, x), SCIPgetSolVal(scip, sol, y), consdata->activity);
4633 SCIP_Real* bestefficacy /**< buffer to store best efficacy of a cut that was added to the LP, if found; or NULL if not of interest */
4664 if( SCIPisGT(scip, consdata->lhsviol, SCIPfeastol(scip)) || SCIPisGT(scip, consdata->rhsviol, SCIPfeastol(scip)) )
4670 violside = SCIPisGT(scip, consdata->lhsviol, SCIPfeastol(scip)) ? SCIP_SIDETYPE_LEFT : SCIP_SIDETYPE_RIGHT;
4673 SCIP_CALL( generateCut(scip, conshdlrdata->exprinterpreter, conss[c], sol, violside, conshdlrdata->cutmaxrange, &row) );
4685 /* if cut is strong enough or it's weak but we separate on a convex function and accept weak cuts there, add cut to SCIP */
4687 (inenforcement && SCIPisGT(scip, efficacy, SCIPfeastol(scip)) && isConvexLocal(scip, conss[c], violside))) &&
4696 SCIPdebugMsg(scip, "cut for constraint <%s> is infeasible -> cutoff.\n", SCIPconsGetName(conss[c]));
4701 SCIPdebugMsg(scip, "added cut with efficacy %g for constraint <%s> violated by %g\n", efficacy, SCIPconsGetName(conss[c]), MAX(consdata->lhsviol, consdata->rhsviol));
4713 SCIPdebugMsg(scip, "abandon cut since efficacy %g is too small or not applicable\n", efficacy);
4723 * others are only checked and enforced if we are still feasible or have not found a separating cut yet
4732 /** processes the event that a new primal solution has been found adds linearizations of all-convex constraints to the cutpool */
4735 {
4766 /* we are only interested in solution coming from some heuristic other than trysol, but not from the tree
4767 * the reason for ignoring trysol solutions is that they may come from an NLP solve in sepalp, where we already added linearizations,
4776 SCIPdebugMsg(scip, "catched new sol event %" SCIP_EVENTTYPE_FORMAT " from heur <%s>; have %d conss\n", SCIPeventGetType(event), SCIPheurGetName(SCIPsolGetHeur(sol)), nconss);
4791 SCIP_CALL( generateLinearizationCut(scip, conshdlrdata->exprinterpreter, conss[c], x0y0, TRUE, &row) );
4808 /** registers unfixed variables in nonlinear terms of violated constraints as external branching candidates
4809 * We score the variables by their gap between the convex envelope and the bivariate function in the current (x,y).
4810 * This value is given by the constraint violation, since we assume that cuts have been generated which support
4835 SCIPdebugMsg(scip, "cons <%s> violation: %g %g\n", SCIPconsGetName(conss[c]), consdata->lhsviol, consdata->rhsviol);
4849 /* regarding left hand side, we are concave in x and convex in y, so branch on x, if not fixed */
4852 SCIPdebugMsg(scip, "register variable x = <%s>[%g,%g] in convex-concave <%s> with violation %g %g\n", SCIPvarGetName(xy[0]), SCIPvarGetLbLocal(xy[0]), SCIPvarGetUbLocal(xy[0]), SCIPconsGetName(conss[c]), consdata->lhsviol, consdata->rhsviol);
4859 /* regarding right hand side, we are convex in x and concave in y, so branch on y, if not fixed */
4862 SCIPdebugMsg(scip, "register variable y = <%s>[%g,%g] in convex-concave <%s> with violation %g %g\n", SCIPvarGetName(xy[1]), SCIPvarGetLbLocal(xy[1]), SCIPvarGetUbLocal(xy[1]), SCIPconsGetName(conss[c]), consdata->lhsviol, consdata->rhsviol);
4873 if( SCIPisEQ(scip, SCIPvarGetLbLocal(xy[0]), SCIPvarGetUbLocal(xy[0])) || SCIPisEQ(scip, SCIPvarGetLbLocal(xy[1]), SCIPvarGetUbLocal(xy[1])) )
4879 SCIPdebugMsg(scip, "register variable x = <%s>[%g,%g] in 1-convex <%s> with violation %g %g\n", SCIPvarGetName(xy[0]), SCIPvarGetLbLocal(xy[0]), SCIPvarGetUbLocal(xy[0]), SCIPconsGetName(conss[c]), consdata->lhsviol, consdata->rhsviol);
4886 SCIPdebugMsg(scip, "register variable y = <%s>[%g,%g] in 1-convex <%s> with violation %g %g\n", SCIPvarGetName(xy[1]), SCIPvarGetLbLocal(xy[1]), SCIPvarGetUbLocal(xy[1]), SCIPconsGetName(conss[c]), consdata->lhsviol, consdata->rhsviol);
4905 SCIPdebugMsg(scip, "register variable x = <%s>[%g,%g] in allconvex <%s> with violation %g %g\n", SCIPvarGetName(xy[0]), SCIPvarGetLbLocal(xy[0]), SCIPvarGetUbLocal(xy[0]), SCIPconsGetName(conss[c]), consdata->lhsviol, consdata->rhsviol);
4912 SCIPdebugMsg(scip, "register variable y = <%s>[%g,%g] in allconvex <%s> with violation %g %g\n", SCIPvarGetName(xy[1]), SCIPvarGetLbLocal(xy[1]), SCIPvarGetUbLocal(xy[1]), SCIPconsGetName(conss[c]), consdata->lhsviol, consdata->rhsviol);
4923 /** registers a nonlinear variable from a violated constraint as branching candidate that has a large absolute value in the relaxation */
4953 if( !SCIPisGT(scip, consdata->lhsviol, SCIPfeastol(scip)) && !SCIPisGT(scip, consdata->rhsviol, SCIPfeastol(scip)) )
4979 /** enforces violated bivariate constraints where both nonlinear variables can be assumed to be fixed
5011 if( !SCIPisGT(scip, consdata->lhsviol, SCIPfeastol(scip)) && !SCIPisGT(scip, consdata->rhsviol, SCIPfeastol(scip)) )
5018 /* if all variables are fixed (at least up to epsilson), then the activity of the nonlinear part should be bounded */
5040 SCIPdebugMsg(scip, "Linear constraint with one variable: %g <= %g <%s> <= %g\n", lhs, coef, SCIPvarGetName(consdata->z), rhs);
5064 SCIPdebugMsg(scip, "Linear constraint is a bound: %g <= <%s> <= %g\n", lhs, SCIPvarGetName(consdata->z), rhs);
5134 SCIPdebugMsg(scip, "found <%s> infeasible due to domain propagation for variable <%s>\n", cons != NULL ? SCIPconsGetName(cons) : "???", SCIPvarGetName(var)); /*lint !e585*/
5139 if( !SCIPisInfinity(scip, -SCIPintervalGetInf(bounds)) && SCIPvarGetStatus(var) != SCIP_VARSTATUS_MULTAGGR )
5145 SCIPdebugMsg(scip, "found <%s> infeasible due to domain propagation for variable <%s>\n", cons != NULL ? SCIPconsGetName(cons) : "???", SCIPvarGetName(var)); /*lint !e585*/
5151 SCIPdebugMsg(scip, "tightened lower bound of variable <%s> in constraint <%s> to %g\n", SCIPvarGetName(var), cons != NULL ? SCIPconsGetName(cons) : "???", SCIPvarGetLbLocal(var)); /*lint !e585*/
5157 if( !SCIPisInfinity(scip, SCIPintervalGetSup(bounds)) && SCIPvarGetStatus(var) != SCIP_VARSTATUS_MULTAGGR )
5163 SCIPdebugMsg(scip, "found <%s> infeasible due to domain propagation for variable <%s>\n", cons != NULL ? SCIPconsGetName(cons) : "???", SCIPvarGetName(var)); /*lint !e585*/
5169 SCIPdebugMsg(scip, "tightened upper bound of variable <%s> in constraint <%s> to %g\n", SCIPvarGetName(var), cons != NULL ? SCIPconsGetName(cons) : "???", SCIPvarGetUbLocal(var)); /*lint !e585*/
5188 SCIP_Bool* redundant /**< buffer where to store whether constraint has been found to be redundant */
5216 /* extend interval by epsilon to avoid cutoff in forward propagation if constraint is only almost feasible */
5218 -infty2infty(SCIPinfinity(scip), INTERVALINFTY, -consdata->lhs+SCIPepsilon(scip)), /*lint !e666*/
5219 +infty2infty(SCIPinfinity(scip), INTERVALINFTY, consdata->rhs+SCIPepsilon(scip)) ); /*lint !e666*/
5229 -infty2infty(SCIPinfinity(scip), INTERVALINFTY, -MIN(SCIPvarGetLbLocal(consdata->z), SCIPvarGetUbLocal(consdata->z))), /*lint !e666*/
5230 +infty2infty(SCIPinfinity(scip), INTERVALINFTY, MAX(SCIPvarGetLbLocal(consdata->z), SCIPvarGetUbLocal(consdata->z)))); /*lint !e666*/
5244 SCIPdebugMsg(scip, "found constraint <%s> to be redundant: sides: [%g, %g], activity: [%g, %g]\n",
5245 SCIPconsGetName(cons), consdata->lhs, consdata->rhs, SCIPintervalGetInf(consactivity), SCIPintervalGetSup(consactivity));
5253 SCIPdebugMsg(scip, "found constraint <%s> to be infeasible; sides: [%g, %g], activity: [%g, %g], infeas: %g\n",
5254 SCIPconsGetName(cons), consdata->lhs, consdata->rhs, SCIPintervalGetInf(consactivity), SCIPintervalGetSup(consactivity),
5255 MAX(consdata->lhs - SCIPintervalGetSup(consactivity), SCIPintervalGetInf(consactivity) - consdata->rhs)); /*lint !e666*/
5277 -infty2infty(SCIPinfinity(scip), INTERVALINFTY, -MIN(SCIPvarGetLbLocal(consdata->z), SCIPvarGetUbLocal(consdata->z))), /*lint !e666*/
5278 +infty2infty(SCIPinfinity(scip), INTERVALINFTY, MAX(SCIPvarGetLbLocal(consdata->z), SCIPvarGetUbLocal(consdata->z)))); /*lint !e666*/
5285 SCIPexprgraphTightenNodeBounds(conshdlrdata->exprgraph, consdata->exprgraphnode, tmp, 0.05, INTERVALINFTY, &cutoff);
5288 SCIPdebugMsg(scip, "found constraint <%s> infeasible%s\n", SCIPconsGetName(cons), SCIPinProbing(scip) ? " in probing" : "");
5305 int* ndelconss /**< buffer where to increase if a constraint was deleted (locally) due to redundancy */
5360 SCIPdebugMsg(scip, "starting domain propagation round %d for %d constraints\n", roundnr, nconss);
5366 * @todo could give FALSE if no linear variable in the constraints had been relaxed since last time
5368 SCIP_CALL( SCIPexprgraphPropagateVarBounds(conshdlrdata->exprgraph, INTERVALINFTY, roundnr == 0, &domainerror) );
5412 SCIPdebugMsg(scip, "backward propagation found problem infeasible%s\n", SCIPinProbing(scip) ? " in probing" : "");
5424 SCIP_CALL( propagateBoundsTightenVar(scip, vars[i], SCIPexprgraphGetNodeBounds(varnodes[i]), NULL, &propresult, nchgbds) );
5438 /** Given a solution where every bivariate constraint is either feasible or can be made feasible by
5439 * moving the linear variable, construct the corresponding feasible solution and pass it to the trysol heuristic.
5440 * The method assumes that this is always possible and that not all constraints are feasible already.
5449 SCIP_Bool* success /**< buffer to store whether we succeeded to construct a solution that satisfies all provided constraints */
5493 /* recompute violation of constraint in case solution newsol is not identical to sol anymore */
5528 SCIPdebugMsg(scip, "increase <%s> by %g to %g\n", SCIPvarGetName(var), delta, SCIPgetSolVal(scip, newsol, var));
5560 SCIPdebugMsg(scip, "increase <%s> by %g to %g\n", SCIPvarGetName(var), delta, SCIPgetSolVal(scip, newsol, var));
5575 if( SCIPisGT(scip, consdata->lhsviol, SCIPfeastol(scip)) || SCIPisGT(scip, consdata->rhsviol, SCIPfeastol(scip)) )
5579 if( !SCIPisInfinity(scip, SCIPgetUpperbound(scip)) && !SCIPisSumLT(scip, SCIPgetSolTransObj(scip, newsol), SCIPgetUpperbound(scip)) )
5583 /* if we have a solution that should satisfy all nonlinear constraints and has a better objective than the current upper bound,
5587 SCIPdebugMsg(scip, "pass solution with objective value %g to trysol heuristic\n", SCIPgetSolTransObj(scip, newsol));
5599 * lhs <= xsqrcoef * x^2 + xlincoef * x + ysqrcoef * y^2 + ylincoef * y + bilincoef * x*y + zcoef * z <= rhs
5729 SCIP_CALL( SCIPexprCreateQuadratic(SCIPblkmem(scip), &e, 2, children, 0.0, (coefx != 0.0 || coefy != 0.0) ? lincoefs : NULL, nquadelems, quadelems) ); /*lint !e826*/
5751 SCIPdebugMsg(scip, "upgrading constraint <%s> to bivariate constraint <%s> with convexity type %d\n", SCIPconsGetName(srccons), name, convextype);
5766 /** creates expression tree for monomial of the form coef * x^p * y^q with x >= 0 and y >= 0 and checks its convexity type */
5799 *mult = coef < 0.0 ? -1.0 : 1.0; /* for the check, assume that monomial has positive coefficient */
5807 else if( (p > 1.0 && q > 1.0) || (p + q < 1.0 && ((p > 1.0 && q < 0.0) || (p < 0.0 && q > 1.0))) )
5849 assert(*convextype != SCIP_BIVAR_UNKNOWN); /* there should be no case where this can still happen */
5870 SCIP_CALL( SCIPexprCreateMonomial(SCIPblkmem(scip), &monomial, *mult*coef, 2, childidxs, exponents) );
5872 SCIP_CALL( SCIPexprCreatePolynomial(SCIPblkmem(scip), &e, 2, children, 1, &monomial, 0.0, FALSE) );
5881 /** creates bivariate constraint from monomial of the form coef * x^p * y^q with x >= 0 and y >= 0
5916 SCIP_CALL( createExprtreeFromMonomial(scip, x, y, coef, p, q, &exprtree, &mult, &convextype) );
5931 SCIPdebugMsg(scip, "upgrading monomial %g<%s>^%g<%s>^%g from constraint <%s> to bivariate constraint with convexity type %d\n", /*lint !e585*/
5932 coef, SCIPvarGetName(x), p, SCIPvarGetName(y), q, srccons != NULL ? SCIPconsGetName(srccons) : "n/a", convextype); /*lint !e585*/
5965 SCIP_Bool solinfeasible, /**< was the solution already declared infeasible by a constraint handler? */
5998 /* if we are above the 100'th enforcement round for this node, something is strange (maybe the relaxation does not
5999 * think that the cuts we add are violated, or we do ECP on a high-dimensional convex function) in this case, check
6000 * if some limit is hit or SCIP should stop for some other reason and terminate enforcement by creating a dummy node
6001 * (in optimized more, returning SCIP_INFEASIBLE in *result would be sufficient, but in debug mode this would give an
6002 * assert in scip.c) the reason to wait for 100 rounds is to avoid calls to SCIPisStopped in normal runs, which may
6013 SCIP_CALL( SCIPcreateChild(scip, &child, 1.0, SCIPnodeGetEstimate(SCIPgetCurrentNode(scip))) );
6033 SCIPdebugMsg(scip, "enforcement with max violation %g in cons <%s> for %s solution\n", maxviol, SCIPconsGetName(maxviolcons),
6045 /* we would like a cut that is efficient enough that it is not redundant in the LP (>lpfeastol)
6047 * thus, in the latter case, we are also happy if the efficacy is at least, say, 75% of the maximal violation
6052 SCIP_CALL( separatePoint(scip, conshdlr, conss, nconss, nusefulconss, sol, minefficacy, TRUE, &separateresult,
6056 SCIPdebugMessage("separation succeeded (bestefficacy = %g, minefficacy = %g, cutoff = %d)\n", sepaefficacy,
6066 SCIPdebugMsg(scip, "separation failed (bestefficacy = %g < %g = minefficacy ); max viol: %g\n", sepaefficacy,
6076 SCIP_CALL( separatePoint(scip, conshdlr, conss, nconss, nusefulconss, sol, leastpossibleefficacy, TRUE,
6087 /* fallback 2: separation probably failed because of numerical difficulties with a convex constraint;
6088 * if noone declared solution infeasible yet and we had not even found a weak cut, try to resolve by branching
6094 /* fallback 3: all nonlinear variables in all violated constraints seem to be fixed -> treat as linear
6101 /* if the linear constraints are actually feasible, then adding them and returning SCIP_CONSADDED confuses SCIP
6102 * when it enforces the new constraints again and nothing resolves the infeasiblity that we declare here thus,
6103 * we only add them if considered violated, and otherwise claim the solution is feasible (but print a warning)
6112 SCIPwarningMessage(scip, "could not enforce feasibility by separating or branching; declaring solution with viol %g as feasible\n", maxviol);
6118 SCIPdebugMsg(scip, "Could not find any usual branching variable candidate. Proposed variable <%s> with LP value %g for branching.\n",
6148 /** destructor of constraint handler to free constraint handler data (called when SCIP is exiting) */
6194 /** deinitialization method of constraint handler (called before transformed problem is freed) */
6212 /** presolving initialization method of constraint handler (called when presolving is about to begin) */
6227 /* reset may{in,de}creasez to FALSE in case some values are still set from a previous solve round */
6238 /** presolving deinitialization method of constraint handler (called after presolving has been finished) */
6278 assert(consdata->z == NULL || SCIPvarIsActive(consdata->z) || SCIPvarGetStatus(consdata->z) == SCIP_VARSTATUS_MULTAGGR);
6289 /** solving process initialization method of constraint handler (called when branch and bound process is about to begin) */
6360 consdata->convextype == SCIP_BIVAR_ALLCONVEX ? SCIP_EXPRCURV_CONVEX : SCIP_EXPRCURV_UNKNOWN) ); /*lint !e826 !e613*/
6385 SCIP_CALL( SCIPcatchEvent(scip, SCIP_EVENTTYPE_SOLFOUND, eventhdlr, (SCIP_EVENTDATA*)conshdlr, &conshdlrdata->newsoleventfilterpos) );
6407 SCIPverbMessage(scip, SCIP_VERBLEVEL_HIGH, NULL, "%4d left and %4d right bivariate constraints of type [%s]\n", nconvextypeslhs[c], nconvextypesrhs[c], typename);
6419 /** solving process deinitialization method of constraint handler (called before branch and bound process data is freed) */
6439 SCIP_CALL( SCIPdropEvent(scip, SCIP_EVENTTYPE_SOLFOUND, eventhdlr, (SCIP_EVENTDATA*)conshdlr, conshdlrdata->newsoleventfilterpos) );
6471 /* expression should have been removed from expression graph when constraint was deactivated */
6511 SCIPconsIsInitial(sourcecons), SCIPconsIsSeparated(sourcecons), SCIPconsIsEnforced(sourcecons),
6513 SCIPconsIsModifiable(sourcecons), SCIPconsIsDynamic(sourcecons), SCIPconsIsRemovable(sourcecons),
6519 /** LP initialization method of constraint handler (called before the initial LP relaxation at a node is solved) */
6571 * For a missing bound, we either reflect the other bound at 0.0 if finite and on the right side,
6622 SCIPvarGetLbGlobal(SCIPexprtreeGetVars(consdata->f)[0]), SCIPvarGetUbGlobal(SCIPexprtreeGetVars(consdata->f)[0]),
6624 SCIPvarGetLbGlobal(SCIPexprtreeGetVars(consdata->f)[1]), SCIPvarGetUbGlobal(SCIPexprtreeGetVars(consdata->f)[1])
6632 if( !SCIPisInfinity(scip, -consdata->lhs) && !unbounded[0] && !unbounded[1] && (ix == 0 || ix == nref-1) && (iy == 0 || iy == nref-1) )
6638 SCIP_CALL( generateOverestimatingHyperplaneCut(scip, conshdlrdata->exprinterpreter, conss[c], xy, &row1) ); /*lint !e613*/
6643 SCIP_CALL( generateLinearizationCut(scip, conshdlrdata->exprinterpreter, conss[c], xy, TRUE, &row2) ); /*lint !e613*/
6653 SCIP_CALL( generateConvexConcaveEstimator(scip, conshdlrdata->exprinterpreter, conss[c], xy, SCIP_SIDETYPE_LEFT, &row1) ); /*lint !e613*/
6658 SCIP_CALL( generateConvexConcaveEstimator(scip, conshdlrdata->exprinterpreter, conss[c], xy, SCIP_SIDETYPE_RIGHT, &row2) ); /*lint !e613*/
6665 if( !SCIPisInfinity(scip, -consdata->lhs) && !unbounded[0] && !unbounded[1] && (ix == 0 || ix == nref-1) && (iy == 0 || iy == nref-1) )
6671 SCIP_CALL( generateOverestimatingHyperplaneCut(scip, conshdlrdata->exprinterpreter, conss[c], xy, &row1) ); /*lint !e613*/
6675 SCIP_CALL( generate1ConvexIndefiniteUnderestimator(scip, conshdlrdata->exprinterpreter, conss[c], xy, &row2) ); /*lint !e613*/
6682 SCIPwarningMessage(scip, "initlp for convexity type %d not implemented\n", consdata->convextype);
6689 if( SCIPgetRowMaxCoef(scip, row1) / SCIPgetRowMinCoef(scip, row1) > conshdlrdata->cutmaxrange )
6691 SCIPdebugMsg(scip, "drop row1 for constraint <%s> because range of coefficients is too large: mincoef = %g, maxcoef = %g -> range = %g\n",
6692 SCIPconsGetName(conss[c]), SCIPgetRowMinCoef(scip, row1), SCIPgetRowMaxCoef(scip, row1), SCIPgetRowMaxCoef(scip, row1) / SCIPgetRowMinCoef(scip, row1)); /*lint !e613*/
6698 SCIPdebugMsg(scip, "drop row1 for constraint <%s> because of very large lhs: %g\n", SCIPconsGetName(conss[c]), SCIProwGetLhs(row1)); /*lint !e613*/
6711 if( SCIPgetRowMaxCoef(scip, row2) / SCIPgetRowMinCoef(scip, row2) > conshdlrdata->cutmaxrange )
6713 SCIPdebugMsg(scip, "drop row2 for constraint <%s> because range of coefficients is too large: mincoef = %g, maxcoef = %g -> range = %g\n",
6714 SCIPconsGetName(conss[c]), SCIPgetRowMinCoef(scip, row2), SCIPgetRowMaxCoef(scip, row2), SCIPgetRowMaxCoef(scip, row2) / SCIPgetRowMinCoef(scip, row2)); /*lint !e613*/
6720 SCIPdebugMsg(scip, "drop row2 for constraint <%s> because of very large rhs: %g\n", SCIPconsGetName(conss[c]), SCIProwGetLhs(row2)); /*lint !e613*/
6759 SCIP_CALL( separatePoint(scip, conshdlr, conss, nconss, nusefulconss, NULL, SCIPgetSepaMinEfficacy(scip), FALSE, result, NULL) );
6782 SCIP_CALL( separatePoint(scip, conshdlr, conss, nconss, nusefulconss, sol, SCIPgetSepaMinEfficacy(scip), FALSE, result, NULL) );
6791 SCIP_CALL( enforceConstraint(scip, conshdlr, conss, nconss, nusefulconss, NULL, solinfeasible, result) );
6800 SCIP_CALL( enforceConstraint(scip, conshdlr, conss, nconss, nusefulconss, sol, solinfeasible, result) );
6854 if( !SCIPisGT(scip, consdata->lhsviol, SCIPfeastol(scip)) && !SCIPisGT(scip, consdata->rhsviol, SCIPfeastol(scip)) )
6857 /* if nonlinear variables are fixed, z should be propagated such that the constraint becomes feasible,
6860 if( consdata->z != NULL && !SCIPisRelEQ(scip, SCIPvarGetLbLocal(consdata->z), SCIPvarGetUbLocal(consdata->z)) )
6862 SCIP_CALL( SCIPaddExternBranchCand(scip, consdata->z, MAX(consdata->lhsviol, consdata->rhsviol), SCIP_INVALID) );
6871 SCIP_CALL( SCIPaddExternBranchCand(scip, var, MAX(consdata->lhsviol, consdata->rhsviol), SCIP_INVALID) );
6879 SCIPdebugMsg(scip, "All variables in violated constraints fixed (up to epsilon). Cannot find branching candidate. Forcing solution of LP.\n");
6917 if( SCIPisGT(scip, consdata->lhsviol, SCIPfeastol(scip)) || SCIPisGT(scip, consdata->rhsviol, SCIPfeastol(scip)) )
6925 SCIPinfoMessage(scip, NULL, "violation: left hand side is violated by %.15g\n", consdata->lhsviol);
6929 SCIPinfoMessage(scip, NULL, "violation: right hand side is violated by %.15g\n", consdata->rhsviol);
6939 /* do not try to shift linear variables if activity is at infinity (leads to setting variable to infinity in solution, which is not allowed) */
6949 if( !(consdata->mayincreasez && consdata->zcoef > 0.0) && !(consdata->maydecreasez && consdata->zcoef < 0.0) )
6957 if( !(consdata->mayincreasez && consdata->zcoef < 0.0) && !(consdata->maydecreasez && consdata->zcoef > 0.0) )
6975 if( *result == SCIP_INFEASIBLE && conshdlrdata->subnlpheur != NULL && sol != NULL && !SCIPisInfinity(scip, maxviol) )
7141 SCIPdebugMsg(scip, "activate %scons <%s>\n", SCIPconsIsTransformed(cons) ? "transformed " : "", SCIPconsGetName(cons));
7144 SCIP_CALL( SCIPexprgraphAddExprtreeSum(conshdlrdata->exprgraph, 1, &consdata->f, NULL, &consdata->exprgraphnode, &exprtreeisnew) );
7147 /* mark that variables in constraint should not be multiaggregated (bad for bound tightening and branching) */
7184 SCIPdebugMsg(scip, "deactivate %scons <%s>\n", SCIPconsIsTransformed(cons) ? "transformed " : "", SCIPconsGetName(cons));
7212 SCIPdebugMsg(scip, "enable %scons <%s>\n", SCIPconsIsTransformed(cons) ? "transformed " : "", SCIPconsGetName(cons));
7243 SCIPdebugMsg(scip, "disable %scons <%s>\n", SCIPconsIsTransformed(cons) ? "transformed " : "", SCIPconsGetName(cons));
7341 SCIP_CALL( SCIPgetVarCopy(sourcescip, scip, consdata->z, &z, varmap, consmap, global, valid) );
7349 SCIP_CALL( SCIPgetVarCopy(sourcescip, scip, SCIPexprtreeGetVars(consdata->f)[0], &xy[0], varmap, consmap, global, valid) );
7355 SCIP_CALL( SCIPgetVarCopy(sourcescip, scip, SCIPexprtreeGetVars(consdata->f)[1], &xy[1], varmap, consmap, global, valid) );
7371 initial, separate, enforce, check, propagate, local, modifiable, dynamic, removable, stickingatnode) );
7407 /** constraint method of constraint handler which returns the number of variables (if possible) */
7503 x, y, z, coefxx, coefx, coefyy, coefy, coefxy, zcoef, SCIPgetLhsQuadratic(scip, cons), SCIPgetRhsQuadratic(scip, cons)) );
7526 /* check if we find at least one bilinear term for which we would create a bivariate constraint
7527 * thus, we search for a variable that has a square term and is involved in at least one bivariate term */
7561 /* require enough space here already, so we do not create and add aux vars that we cannot get rid of easily later */
7568 /* initial remaining quadratic constraint: take linear part and constraint sides from original constraint */
7570 SCIPgetNLinearVarsQuadratic(scip, cons), SCIPgetLinearVarsQuadratic(scip, cons), SCIPgetCoefsLinearVarsQuadratic(scip, cons),
7578 /* remember for each quadratic variable whether its linear and square part has been moved into a bivariate constraint */
7584 /* check for each bilinear term, whether we want to create a bivariate constraint for it and associated square terms */
7647 /* need to enforce new constraints, as relation auxvar = f(x,y) is not redundant, even if original constraint is */
7660 SCIP_CALL( SCIPdebugAddSolVal(scip, auxvar, coefxx * xval * xval + coefyy * yval * yval + coefxy * xval * yval + coefx * xval + coefy * yval) );
7677 /* complete quadcons: check for unmarked quadvarterms and add their linear and square coefficients to quadcons */
7686 * if the variable appears in a bilinear term, then this term should have been added to quadcons above, so the variable is there
7699 SCIP_CALL( SCIPaddQuadVarQuadratic(scip, quadcons, x, quadvarterms[i].lincoef, quadvarterms[i].sqrcoef) );
7726 SCIPgetNLinearVarsQuadratic(scip, cons), SCIPgetLinearVarsQuadratic(scip, cons), SCIPgetCoefsLinearVarsQuadratic(scip, cons),
7752 {
7770 /* could also upgrade bivariate quadratic, but if we don't then node will appear in cons_quadratic later, from which we also upgrade...
7779 /* we are only interested in monomials that are not convex or concave, since cons_nonlinear can handle these the same was as we do */
7786 /* @todo we could also do some more complex reformulation for n-variate monomials, something better than what reformMonomial in cons_nonlinear is doing */
7798 /* so far only support variables as arguments @todo could allow more here, e.g., f(x)^pg(y)^q */
7808 if( SCIPisNegative(scip, SCIPvarGetLbGlobal(x)) || SCIPisNegative(scip, SCIPvarGetLbGlobal(y)) )
7815 SCIP_CALL( SCIPcreateVar(scip, &auxvar, name, SCIPexprgraphGetNodeBounds(node).inf, SCIPexprgraphGetNodeBounds(node).sup,
7821 SCIPexprGetMonomialCoef(monomial), expx, expy, -1.0, -SCIPexprgraphGetNodePolynomialConstant(node), -SCIPexprgraphGetNodePolynomialConstant(node)) );
7885 SCIP_CALL( SCIPsetConshdlrPresol(scip, conshdlr, consPresolBivariate, CONSHDLR_MAXPREROUNDS, CONSHDLR_PRESOLTIMING) );
7887 SCIP_CALL( SCIPsetConshdlrProp(scip, conshdlr, consPropBivariate, CONSHDLR_PROPFREQ, CONSHDLR_DELAYPROP,
7889 SCIP_CALL( SCIPsetConshdlrSepa(scip, conshdlr, consSepalpBivariate, consSepasolBivariate, CONSHDLR_SEPAFREQ,
7895 SCIP_CALL( SCIPincludeQuadconsUpgrade(scip, quadconsUpgdBivariate, QUADCONSUPGD_PRIORITY, FALSE, CONSHDLR_NAME) );
7898 SCIP_CALL( SCIPincludeNonlinconsUpgrade(scip, NULL, exprgraphnodeReformBivariate, NONLINCONSUPGD_PRIORITY, FALSE, CONSHDLR_NAME) );
7902 "maximal coef range of a cut (maximal coefficient divided by minimal coefficient) in order to be added to LP relaxation",
7906 "whether to try to make solutions in check function feasible by shifting a linear variable (esp. useful if constraint was actually objective function)",
7910 "limit on number of propagation rounds for a single constraint within one round of SCIP propagation",
7914 "number of reference points in each direction where to compute linear support for envelope in LP initialization",
7922 SCIP_CALL( SCIPincludeEventhdlrBasic(scip, &(conshdlrdata->linvareventhdlr), CONSHDLR_NAME"_boundchange", "signals a bound tightening in a linear variable to a bivariate constraint",
7927 SCIP_CALL( SCIPincludeEventhdlrBasic(scip, &(conshdlrdata->nonlinvareventhdlr), CONSHDLR_NAME"_boundchange2", "signals a bound change in a nonlinear variable to the bivariate constraint handler",
7931 SCIP_CALL( SCIPincludeEventhdlrBasic(scip, NULL, CONSHDLR_NAME"_newsolution", "handles the event that a new primal solution has been found",
7950 * @note the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()
7980 SCIP_Bool removable, /**< should the relaxation be removed from the LP due to aging or cleanup?
7982 SCIP_Bool stickingatnode /**< should the constraint always be kept at the node where it was added, even
8022 SCIP_CALL( SCIPcreateCons(scip, cons, name, conshdlr, consdata, initial, separate, enforce, check, propagate,
8029 * in its most basic version, i. e., all constraint flags are set to their basic value as explained for the
8030 * method SCIPcreateConsBivariate(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h
8034 * @note the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()
SCIP_RETCODE SCIPupdateStartpointHeurSubNlp(SCIP *scip, SCIP_HEUR *heur, SCIP_SOL *solcand, SCIP_Real violation)
Definition: heur_subnlp.c:2451
static SCIP_DECL_CONSENFOLP(consEnfolpBivariate)
Definition: cons_bivariate.c:6790
SCIP_Bool SCIPisEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:436
void SCIPintervalDivScalar(SCIP_Real infinity, SCIP_INTERVAL *resultant, SCIP_INTERVAL operand1, SCIP_Real operand2)
Definition: intervalarith.c:1083
SCIP_Real SCIPexprgraphGetNodeVal(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13338
static SCIP_RETCODE createExprtreeFromMonomial(SCIP *scip, SCIP_VAR *x, SCIP_VAR *y, SCIP_Real coef, SCIP_Real p, SCIP_Real q, SCIP_EXPRTREE **exprtree, SCIP_Real *mult, SCIP_BIVAR_CONVEXITY *convextype)
Definition: cons_bivariate.c:5769
SCIP_RETCODE SCIPexprgraphPropagateVarBounds(SCIP_EXPRGRAPH *exprgraph, SCIP_Real infinity, SCIP_Bool clearreverseprop, SCIP_Bool *domainerror)
Definition: expr.c:15844
SCIP_Bool SCIPisRelEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:1147
SCIP_RETCODE SCIPexprgraphReplaceVarByLinearSum(SCIP_EXPRGRAPH *exprgraph, void *var, int ncoefs, SCIP_Real *coefs, void **vars, SCIP_Real constant)
Definition: expr.c:15525
Definition: type_result.h:33
static SCIP_RETCODE catchLinearVarEvents(SCIP *scip, SCIP_CONS *cons)
Definition: cons_bivariate.c:197
Definition: type_result.h:37
static SCIP_RETCODE computeViolation(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS *cons, SCIP_SOL *sol)
Definition: cons_bivariate.c:780
SCIP_RETCODE SCIPcreateChild(SCIP *scip, SCIP_NODE **node, SCIP_Real nodeselprio, SCIP_Real estimate)
Definition: scip_branch.c:959
static SCIP_RETCODE generateConvexConcaveEstimator(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_CONS *cons, SCIP_Real xyref[2], SCIP_SIDETYPE violside, SCIP_ROW **row)
Definition: cons_bivariate.c:3343
void SCIPexprgraphSetVarNodeValue(SCIP_EXPRGRAPHNODE *varnode, SCIP_Real value)
Definition: expr.c:14980
SCIP_RETCODE SCIPheurPassSolTrySol(SCIP *scip, SCIP_HEUR *heur, SCIP_SOL *sol)
Definition: heur_trysol.c:242
SCIP_RETCODE SCIPsetConshdlrTrans(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSTRANS((*constrans)))
Definition: scip_cons.c:585
SCIP_RETCODE SCIPexprSubstituteVars(BMS_BLKMEM *blkmem, SCIP_EXPR *expr, SCIP_EXPR **substexprs)
Definition: expr.c:8146
SCIP_Bool SCIPintervalIsEmpty(SCIP_Real infinity, SCIP_INTERVAL operand)
Definition: intervalarith.c:405
SCIP_Real SCIPgetLinearCoefBivariate(SCIP *scip, SCIP_CONS *cons)
Definition: cons_bivariate.c:8070
primal heuristic that tries a given solution
SCIP_EXPORT SCIP_RETCODE SCIPexprintNewParametrization(SCIP_EXPRINT *exprint, SCIP_EXPRTREE *tree)
Definition: exprinterpret_cppad.cpp:2276
SCIP_RETCODE SCIPaddExternBranchCand(SCIP *scip, SCIP_VAR *var, SCIP_Real score, SCIP_Real solval)
Definition: scip_branch.c:654
SCIP_CONSHDLR * SCIPfindConshdlr(SCIP *scip, const char *name)
Definition: scip_cons.c:876
static SCIP_DECL_CONSPRESOL(consPresolBivariate)
Definition: cons_bivariate.c:7003
Definition: intervalarith.h:37
public methods for SCIP parameter handling
static SCIP_DECL_QUADCONSUPGD(quadconsUpgdBivariate)
Definition: cons_bivariate.c:7424
static SCIP_RETCODE initSepaData(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_CONS *cons)
Definition: cons_bivariate.c:1060
SCIP_RETCODE SCIPexprgraphAddVars(SCIP_EXPRGRAPH *exprgraph, int nvars, void **vars, SCIP_EXPRGRAPHNODE **varnodes)
Definition: expr.c:15264
methods to interpret (evaluate) an expression tree "fast"
static SCIP_RETCODE registerLargeRelaxValueVariableForBranching(SCIP *scip, SCIP_CONS **conss, int nconss, SCIP_SOL *sol, SCIP_VAR **brvar)
Definition: cons_bivariate.c:4926
void SCIPexprtreePrint(SCIP_EXPRTREE *tree, SCIP_MESSAGEHDLR *messagehdlr, FILE *file, const char **varnames, const char **paramnames)
Definition: expr.c:8757
public methods for branch and bound tree
SCIP_RETCODE SCIPwriteVarName(SCIP *scip, FILE *file, SCIP_VAR *var, SCIP_Bool type)
Definition: scip_var.c:220
SCIP_RETCODE SCIPsetConshdlrExitsol(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSEXITSOL((*consexitsol)))
Definition: scip_cons.c:452
SCIP_Bool SCIPisGE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:488
Definition: struct_scip.h:58
SCIP_RETCODE SCIPtightenVarLb(SCIP *scip, SCIP_VAR *var, SCIP_Real newbound, SCIP_Bool force, SCIP_Bool *infeasible, SCIP_Bool *tightened)
Definition: scip_var.c:5121
SCIP_RETCODE SCIPcreateCons(SCIP *scip, SCIP_CONS **cons, const char *name, SCIP_CONSHDLR *conshdlr, SCIP_CONSDATA *consdata, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)
Definition: scip_cons.c:933
static SCIP_DECL_EXPRGRAPHNODEREFORM(exprgraphnodeReformBivariate)
Definition: cons_bivariate.c:7752
static SCIP_RETCODE generateOverestimatingHyperplaneCut(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_CONS *cons, SCIP_Real *x0y0, SCIP_ROW **row)
Definition: cons_bivariate.c:1773
SCIP_BILINTERM * SCIPgetBilinTermsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:14976
SCIP_EXPORT int SCIPvarGetNLocksUpType(SCIP_VAR *var, SCIP_LOCKTYPE locktype)
Definition: var.c:3241
public methods for memory management
SCIP_RETCODE SCIPsetConshdlrEnforelax(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSENFORELAX((*consenforelax)))
Definition: scip_cons.c:307
static SCIP_RETCODE propagateBoundsCons(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS *cons, SCIP_RESULT *result, int *nchgbds, SCIP_Bool *redundant)
Definition: cons_bivariate.c:5183
int SCIPexprgraphGetNodeNChildren(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:12974
SCIP_RETCODE SCIPcreateConsBasicBivariate(SCIP *scip, SCIP_CONS **cons, const char *name, SCIP_EXPRTREE *f, SCIP_BIVAR_CONVEXITY convextype, SCIP_VAR *z, SCIP_Real zcoef, SCIP_Real lhs, SCIP_Real rhs)
Definition: cons_bivariate.c:8037
SCIP_RETCODE SCIPmarkConsPropagate(SCIP *scip, SCIP_CONS *cons)
Definition: scip_cons.c:1950
SCIP_RETCODE SCIPincludeConshdlrBasic(SCIP *scip, SCIP_CONSHDLR **conshdlrptr, const char *name, const char *desc, int enfopriority, int chckpriority, int eagerfreq, SCIP_Bool needscons, SCIP_DECL_CONSENFOLP((*consenfolp)), SCIP_DECL_CONSENFOPS((*consenfops)), SCIP_DECL_CONSCHECK((*conscheck)), SCIP_DECL_CONSLOCK((*conslock)), SCIP_CONSHDLRDATA *conshdlrdata)
Definition: scip_cons.c:165
SCIP_RETCODE SCIPaddVarLocksType(SCIP *scip, SCIP_VAR *var, SCIP_LOCKTYPE locktype, int nlocksdown, int nlocksup)
Definition: scip_var.c:4200
static SCIP_RETCODE dropLinearVarEvents(SCIP *scip, SCIP_CONS *cons)
Definition: cons_bivariate.c:250
SCIP_RETCODE SCIPsetConshdlrActive(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSACTIVE((*consactive)))
Definition: scip_cons.c:654
static SCIP_RETCODE removeFixedNonlinearVariables(SCIP *scip, SCIP_CONSHDLR *conshdlr)
Definition: cons_bivariate.c:704
SCIP_RETCODE SCIPgetTransformedVars(SCIP *scip, int nvars, SCIP_VAR **vars, SCIP_VAR **transvars)
Definition: scip_var.c:1483
SCIP_EVENTHDLR * SCIPfindEventhdlr(SCIP *scip, const char *name)
Definition: scip_event.c:224
SCIP_RETCODE SCIPcreateNlRow(SCIP *scip, SCIP_NLROW **nlrow, const char *name, SCIP_Real constant, int nlinvars, SCIP_VAR **linvars, SCIP_Real *lincoefs, int nquadvars, SCIP_VAR **quadvars, int nquadelems, SCIP_QUADELEM *quadelems, SCIP_EXPRTREE *expression, SCIP_Real lhs, SCIP_Real rhs, SCIP_EXPRCURV curvature)
Definition: scip_nlp.c:1167
void SCIPwarningMessage(SCIP *scip, const char *formatstr,...)
Definition: scip_message.c:122
Definition: type_result.h:49
SCIP_RETCODE SCIPsetConshdlrGetVars(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSGETVARS((*consgetvars)))
Definition: scip_cons.c:815
SCIP_RETCODE SCIPaddSquareCoefQuadratic(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, SCIP_Real coef)
Definition: cons_quadratic.c:14712
type definitions for expression interpreter
SCIP_Real SCIPgetSolVal(SCIP *scip, SCIP_SOL *sol, SCIP_VAR *var)
Definition: scip_sol.c:1352
SCIP_RETCODE SCIPtightenVarUb(SCIP *scip, SCIP_VAR *var, SCIP_Real newbound, SCIP_Bool force, SCIP_Bool *infeasible, SCIP_Bool *tightened)
Definition: scip_var.c:5237
SCIP_RETCODE SCIPcheckCurvatureQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:15050
SCIP_RETCODE SCIPprintRow(SCIP *scip, SCIP_ROW *row, FILE *file)
Definition: scip_lp.c:2031
static SCIP_RETCODE computeViolations(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS **conss, int nconss, SCIP_SOL *sol, SCIP_CONS **maxviolcon)
Definition: cons_bivariate.c:912
SCIP_RETCODE SCIPexprCreateMonomial(BMS_BLKMEM *blkmem, SCIP_EXPRDATA_MONOMIAL **monomial, SCIP_Real coef, int nfactors, int *childidxs, SCIP_Real *exponents)
Definition: expr.c:7036
void SCIPexprgraphSetVarNodeBounds(SCIP_EXPRGRAPH *exprgraph, SCIP_EXPRGRAPHNODE *varnode, SCIP_INTERVAL varbounds)
Definition: expr.c:15024
static SCIP_RETCODE separatePoint(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS **conss, int nconss, int nusefulconss, SCIP_SOL *sol, SCIP_Real minefficacy, SCIP_Bool inenforcement, SCIP_RESULT *result, SCIP_Real *bestefficacy)
Definition: cons_bivariate.c:4624
SCIP_RETCODE SCIPsetConshdlrPrint(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSPRINT((*consprint)))
Definition: scip_cons.c:769
Definition: struct_var.h:198
static SCIP_DECL_CONSHDLRCOPY(conshdlrCopyBivariate)
Definition: cons_bivariate.c:6135
Definition: cons_quadratic.h:104
Definition: type_message.h:45
void SCIPverbMessage(SCIP *scip, SCIP_VERBLEVEL msgverblevel, FILE *file, const char *formatstr,...)
Definition: scip_message.c:215
void SCIPexprgraphPropagateNodeBounds(SCIP_EXPRGRAPH *exprgraph, SCIP_Real infinity, SCIP_Real minstrength, SCIP_Bool *cutoff)
Definition: expr.c:15898
SCIP_Real SCIPgetLhsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:14988
SCIP_EXPRGRAPHNODE ** SCIPexprgraphGetVarNodes(SCIP_EXPRGRAPH *exprgraph)
Definition: expr.c:14970
SCIP_QUADVARTERM * SCIPgetQuadVarTermsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:14915
SCIP_Real SCIPgetRhsBivariate(SCIP *scip, SCIP_CONS *cons)
Definition: cons_bivariate.c:8106
SCIP_RETCODE SCIPdelConsLocal(SCIP *scip, SCIP_CONS *cons)
Definition: scip_prob.c:3470
SCIP_EXPORT SCIP_RETCODE SCIPexprintGrad(SCIP_EXPRINT *exprint, SCIP_EXPRTREE *tree, SCIP_Real *varvals, SCIP_Bool new_varvals, SCIP_Real *val, SCIP_Real *gradient)
Definition: exprinterpret_cppad.cpp:2429
SCIP_RETCODE SCIPexprtreeCopy(BMS_BLKMEM *blkmem, SCIP_EXPRTREE **targettree, SCIP_EXPRTREE *sourcetree)
Definition: expr.c:8813
SCIP_Real SCIPgetLhsBivariate(SCIP *scip, SCIP_CONS *cons)
Definition: cons_bivariate.c:8094
SCIP_INTERVAL SCIPexprgraphGetNodeBounds(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13328
SCIP_RETCODE SCIPsetConshdlrDelete(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSDELETE((*consdelete)))
Definition: scip_cons.c:562
void SCIPexprReindexVars(SCIP_EXPR *expr, int *newindices)
Definition: expr.c:8184
void SCIPintervalSetBounds(SCIP_INTERVAL *resultant, SCIP_Real inf, SCIP_Real sup)
Definition: intervalarith.c:380
SCIP_Bool SCIPisFeasLE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:797
static SCIP_RETCODE solveDerivativeEquation(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Real targetvalue, SCIP_Real lb, SCIP_Real ub, SCIP_Real *val, SCIP_Bool *success)
Definition: cons_bivariate.c:1290
public methods for problem variables
static SCIP_DECL_CONSGETNVARS(consGetNVarsBivariate)
Definition: cons_bivariate.c:7410
SCIP_RETCODE SCIPaddBoolParam(SCIP *scip, const char *name, const char *desc, SCIP_Bool *valueptr, SCIP_Bool isadvanced, SCIP_Bool defaultvalue, SCIP_DECL_PARAMCHGD((*paramchgd)), SCIP_PARAMDATA *paramdata)
Definition: scip_param.c:47
Definition: type_expr.h:100
Definition: type_lp.h:55
Definition: type_expr.h:40
SCIP_Bool SCIPintervalIsNegativeInfinity(SCIP_Real infinity, SCIP_INTERVAL operand)
Definition: intervalarith.c:447
Definition: type_result.h:40
SCIP_RETCODE SCIPexprgraphAddExprtreeSum(SCIP_EXPRGRAPH *exprgraph, int nexprtrees, SCIP_EXPRTREE **exprtrees, SCIP_Real *coefs, SCIP_EXPRGRAPHNODE **rootnode, SCIP_Bool *rootnodeisnew)
Definition: expr.c:15384
SCIP_RETCODE SCIPsetConshdlrPresol(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSPRESOL((*conspresol)), int maxprerounds, SCIP_PRESOLTIMING presoltiming)
Definition: scip_cons.c:524
static SCIP_RETCODE createConsFromMonomial(SCIP *scip, SCIP_CONS *srccons, SCIP_CONS **cons, const char *name, SCIP_VAR *x, SCIP_VAR *y, SCIP_VAR *z, SCIP_Real coef, SCIP_Real p, SCIP_Real q, SCIP_Real zcoef, SCIP_Real lhs, SCIP_Real rhs)
Definition: cons_bivariate.c:5886
static SCIP_DECL_CONSACTIVE(consActiveBivariate)
Definition: cons_bivariate.c:7123
SCIP_RETCODE SCIPexprtreeCreate(BMS_BLKMEM *blkmem, SCIP_EXPRTREE **tree, SCIP_EXPR *root, int nvars, int nparams, SCIP_Real *params)
Definition: expr.c:8772
static SCIP_RETCODE generate1ConvexIndefiniteUnderestimatorAtBoundary(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Real xyref[2], SCIP_Real cutcoeff[4], SCIP_Real *convenvvalue, SCIP_Bool *success)
Definition: cons_bivariate.c:3600
static SCIP_RETCODE generateOrthogonal_lx_ly_Underestimator(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Real *xyref, SCIP_Real cutcoeff[4], SCIP_Real *convenvvalue, SCIP_Bool *success)
Definition: cons_bivariate.c:2057
SCIP_RETCODE SCIPsetConshdlrInit(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSINIT((*consinit)))
Definition: scip_cons.c:380
static SCIP_RETCODE createConsFromQuadTerm(SCIP *scip, SCIP_CONS *srccons, SCIP_CONS **cons, const char *name, SCIP_VAR *x, SCIP_VAR *y, SCIP_VAR *z, SCIP_Real coefxx, SCIP_Real coefx, SCIP_Real coefyy, SCIP_Real coefy, SCIP_Real coefxy, SCIP_Real coefz, SCIP_Real lhs, SCIP_Real rhs)
Definition: cons_bivariate.c:5603
SCIP_RETCODE SCIPsetConsEnforced(SCIP *scip, SCIP_CONS *cons, SCIP_Bool enforce)
Definition: scip_cons.c:1257
SCIP_RETCODE SCIPsetConshdlrGetNVars(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSGETNVARS((*consgetnvars)))
Definition: scip_cons.c:838
void SCIPexprtreeSetParamVal(SCIP_EXPRTREE *tree, int paramidx, SCIP_Real paramval)
Definition: expr.c:8643
public methods for SCIP variables
SCIP_RETCODE SCIPsetConshdlrExitpre(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSEXITPRE((*consexitpre)))
Definition: scip_cons.c:500
SCIP_RETCODE SCIPfindQuadVarTermQuadratic(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, int *pos)
Definition: cons_quadratic.c:14944
SCIP_Real SCIPgetRowSolFeasibility(SCIP *scip, SCIP_ROW *row, SCIP_SOL *sol)
Definition: scip_lp.c:2005
public methods for separator plugins
SCIP_EXPRTREE * SCIPgetExprtreeBivariate(SCIP *scip, SCIP_CONS *cons)
Definition: cons_bivariate.c:8082
SCIP_RETCODE SCIPlockVarCons(SCIP *scip, SCIP_VAR *var, SCIP_CONS *cons, SCIP_Bool lockdown, SCIP_Bool lockup)
Definition: scip_var.c:4291
Definition: type_expr.h:46
int SCIPgetNQuadVarTermsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:14901
Definition: struct_tree.h:132
int SCIPexprgraphGetNodePolynomialNMonomials(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13197
SCIP_RETCODE SCIPsetConshdlrFree(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSFREE((*consfree)))
Definition: scip_cons.c:356
public methods for numerical tolerances
SCIP_RETCODE SCIPaddQuadVarQuadratic(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, SCIP_Real lincoef, SCIP_Real sqrcoef)
Definition: cons_quadratic.c:14629
void SCIPupdateSolConsViolation(SCIP *scip, SCIP_SOL *sol, SCIP_Real absviol, SCIP_Real relviol)
Definition: scip_sol.c:264
static SCIP_RETCODE registerBranchingVariables(SCIP *scip, SCIP_CONS **conss, int nconss, int *nnotify)
Definition: cons_bivariate.c:4815
public methods for expressions, expression trees, expression graphs, and related stuff ...
SCIP_Bool SCIPintervalIsPositiveInfinity(SCIP_Real infinity, SCIP_INTERVAL operand)
Definition: intervalarith.c:438
int SCIPexprGetMonomialNFactors(SCIP_EXPRDATA_MONOMIAL *monomial)
Definition: expr.c:5911
public methods for querying solving statistics
Definition: struct_sol.h:63
SCIP_Bool SCIPisLE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:462
static SCIP_DECL_CONSENFORELAX(consEnforelaxBivariate)
Definition: cons_bivariate.c:6799
public methods for the branch-and-bound tree
SCIP_RETCODE SCIPgetVarCopy(SCIP *sourcescip, SCIP *targetscip, SCIP_VAR *sourcevar, SCIP_VAR **targetvar, SCIP_HASHMAP *varmap, SCIP_HASHMAP *consmap, SCIP_Bool global, SCIP_Bool *success)
Definition: scip_copy.c:672
SCIP_RETCODE SCIPaddQuadVarLinearCoefQuadratic(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, SCIP_Real coef)
Definition: cons_quadratic.c:14659
SCIP_EVENTHDLRDATA * SCIPeventhdlrGetData(SCIP_EVENTHDLR *eventhdlr)
Definition: event.c:324
SCIP_EXPROP SCIPexprgraphGetNodeOperator(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13034
SCIP_EXPRDATA_MONOMIAL ** SCIPexprgraphGetNodePolynomialMonomials(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13185
SCIP_RETCODE SCIPexprgraphCreate(BMS_BLKMEM *blkmem, SCIP_EXPRGRAPH **exprgraph, int varssizeinit, int depthinit, SCIP_DECL_EXPRGRAPHVARADDED((*exprgraphvaradded)), SCIP_DECL_EXPRGRAPHVARREMOVE((*exprgraphvarremove)), SCIP_DECL_EXPRGRAPHVARCHGIDX((*exprgraphvarchgidx)), void *userdata)
Definition: expr.c:15092
Definition: type_expr.h:47
SCIP_RETCODE SCIPcreateConsBivariate(SCIP *scip, SCIP_CONS **cons, const char *name, SCIP_EXPRTREE *f, SCIP_BIVAR_CONVEXITY convextype, SCIP_VAR *z, SCIP_Real zcoef, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)
Definition: cons_bivariate.c:7953
Definition: type_expr.h:49
Definition: cons_bivariate.h:77
SCIP_RETCODE SCIPcreateSolCopy(SCIP *scip, SCIP_SOL **sol, SCIP_SOL *sourcesol)
Definition: scip_sol.c:609
SCIP_RETCODE SCIPreleaseNlRow(SCIP *scip, SCIP_NLROW **nlrow)
Definition: scip_nlp.c:1275
SCIP_RETCODE SCIPmarkDoNotMultaggrVar(SCIP *scip, SCIP_VAR *var)
Definition: scip_var.c:8542
public methods for managing constraints
SCIP_RETCODE SCIPgetProbvarLinearSum(SCIP *scip, SCIP_VAR **vars, SCIP_Real *scalars, int *nvars, int varssize, SCIP_Real *constant, int *requiredsize, SCIP_Bool mergemultiples)
Definition: scip_var.c:1740
SCIP_Real SCIPexprgraphGetNodePolynomialConstant(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13209
SCIP_RETCODE SCIPsetConshdlrExit(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSEXIT((*consexit)))
Definition: scip_cons.c:404
SCIP_EXPRCURV SCIPexprgraphGetNodeCurvature(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13348
SCIP_RETCODE SCIPexprCreateQuadratic(BMS_BLKMEM *blkmem, SCIP_EXPR **expr, int nchildren, SCIP_EXPR **children, SCIP_Real constant, SCIP_Real *lincoefs, int nquadelems, SCIP_QUADELEM *quadelems)
Definition: expr.c:6585
Definition: type_result.h:35
Definition: struct_cons.h:37
interval arithmetics for provable bounds
SCIP_Bool SCIPisConvexQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:15063
SCIP_RETCODE SCIPincSolVal(SCIP *scip, SCIP_SOL *sol, SCIP_VAR *var, SCIP_Real incval)
Definition: scip_sol.c:1309
Definition: struct_cons.h:117
static SCIP_RETCODE unlockLinearVariable(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, SCIP_Real coef)
Definition: cons_bivariate.c:444
static SCIP_DECL_CONSINITSOL(consInitsolBivariate)
Definition: cons_bivariate.c:6292
public methods for event handler plugins and event handlers
SCIP_Real SCIPintervalGetInf(SCIP_INTERVAL interval)
Definition: intervalarith.c:352
SCIP_Bool SCIPisFeasEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:771
static SCIP_RETCODE proposeFeasibleSolution(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS **conss, int nconss, SCIP_SOL *sol, SCIP_Bool *success)
Definition: cons_bivariate.c:5444
SCIP_RETCODE SCIPcatchEvent(SCIP *scip, SCIP_EVENTTYPE eventtype, SCIP_EVENTHDLR *eventhdlr, SCIP_EVENTDATA *eventdata, int *filterpos)
Definition: scip_event.c:276
SCIP_RETCODE SCIPexprtreePrintWithNames(SCIP_EXPRTREE *tree, SCIP_MESSAGEHDLR *messagehdlr, FILE *file)
Definition: nlp.c:173
SCIP_RETCODE SCIPexprCopyDeep(BMS_BLKMEM *blkmem, SCIP_EXPR **targetexpr, SCIP_EXPR *sourceexpr)
Definition: expr.c:6142
SCIP_RETCODE SCIPsetConshdlrInitsol(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSINITSOL((*consinitsol)))
Definition: scip_cons.c:428
SCIP_RETCODE SCIPsetConshdlrDisable(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSDISABLE((*consdisable)))
Definition: scip_cons.c:723
SCIP_RETCODE SCIPgetTransformedVar(SCIP *scip, SCIP_VAR *var, SCIP_VAR **transvar)
Definition: scip_var.c:1442
Definition: type_result.h:36
public methods for expression handlers
static SCIP_DECL_CONSDELETE(consDeleteBivariate)
Definition: cons_bivariate.c:6457
static SCIP_DECL_EXPRGRAPHVARADDED(exprgraphVarAdded)
Definition: cons_bivariate.c:349
constraint handler for quadratic constraints
static SCIP_DECL_CONSENFOPS(consEnfopsBivariate)
Definition: cons_bivariate.c:6809
SCIP_EXPORT SCIP_RETCODE SCIPexprintFree(SCIP_EXPRINT **exprint)
Definition: exprinterpret_cppad.cpp:2174
static SCIP_RETCODE propagateBounds(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS **conss, int nconss, SCIP_RESULT *result, int *nchgbds, int *ndelconss)
Definition: cons_bivariate.c:5299
Definition: type_retcode.h:33
public methods for problem copies
public methods for primal CIP solutions
SCIP_RETCODE SCIPcreateConsNonlinear(SCIP *scip, SCIP_CONS **cons, const char *name, int nlinvars, SCIP_VAR **linvars, SCIP_Real *lincoefs, int nexprtrees, SCIP_EXPRTREE **exprtrees, SCIP_Real *nonlincoefs, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)
Definition: cons_nonlinear.c:9363
SCIP_RETCODE SCIPsetConshdlrInitpre(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSINITPRE((*consinitpre)))
Definition: scip_cons.c:476
static SCIP_DECL_EXPRGRAPHVARREMOVE(exprgraphVarRemove)
Definition: cons_bivariate.c:387
SCIP_RETCODE SCIPaddBilinTermQuadratic(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var1, SCIP_VAR *var2, SCIP_Real coef)
Definition: cons_quadratic.c:14769
SCIP_RETCODE SCIPexprCreatePolynomial(BMS_BLKMEM *blkmem, SCIP_EXPR **expr, int nchildren, SCIP_EXPR **children, int nmonomials, SCIP_EXPRDATA_MONOMIAL **monomials, SCIP_Real constant, SCIP_Bool copymonomials)
Definition: expr.c:6633
static SCIP_RETCODE lockLinearVariable(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, SCIP_Real coef)
Definition: cons_bivariate.c:413
SCIP_RETCODE SCIPcreateConsQuadratic2(SCIP *scip, SCIP_CONS **cons, const char *name, int nlinvars, SCIP_VAR **linvars, SCIP_Real *lincoefs, int nquadvarterms, SCIP_QUADVARTERM *quadvarterms, int nbilinterms, SCIP_BILINTERM *bilinterms, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable)
Definition: cons_quadratic.c:14482
Definition: type_result.h:42
SCIP_RETCODE SCIPincludeQuadconsUpgrade(SCIP *scip, SCIP_DECL_QUADCONSUPGD((*quadconsupgd)), int priority, SCIP_Bool active, const char *conshdlrname)
Definition: cons_quadratic.c:14193
void SCIPintervalSet(SCIP_INTERVAL *resultant, SCIP_Real value)
Definition: intervalarith.c:368
void SCIPexprgraphTightenNodeBounds(SCIP_EXPRGRAPH *exprgraph, SCIP_EXPRGRAPHNODE *node, SCIP_INTERVAL nodebounds, SCIP_Real minstrength, SCIP_Real infinity, SCIP_Bool *cutoff)
Definition: expr.c:14707
static SCIP_RETCODE freeSepaData(SCIP *scip, SCIP_CONS *cons)
Definition: cons_bivariate.c:1216
static SCIP_RETCODE enforceConstraint(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS **conss, int nconss, int nusefulconss, SCIP_SOL *sol, SCIP_Bool solinfeasible, SCIP_RESULT *result)
Definition: cons_bivariate.c:5959
Definition: cons_bivariate.h:79
SCIP_VAR ** SCIPgetLinearVarsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:14874
Definition: struct_heur.h:79
SCIP_EXPORT SCIP_RETCODE SCIPexprintCreate(BMS_BLKMEM *blkmem, SCIP_EXPRINT **exprint)
Definition: exprinterpret_cppad.cpp:2157
public methods for primal heuristic plugins and divesets
public methods for constraint handler plugins and constraints
public methods for NLP management
Definition: type_retcode.h:34
static SCIP_DECL_CONSDEACTIVE(consDeactiveBivariate)
Definition: cons_bivariate.c:7167
Definition: struct_expr.h:46
static SCIP_DECL_EVENTEXEC(processLinearVarEvent)
Definition: cons_bivariate.c:177
static SCIP_DECL_CONSSEPALP(consSepalpBivariate)
Definition: cons_bivariate.c:6743
SCIP_RETCODE SCIPsetConshdlrSepa(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSSEPALP((*conssepalp)), SCIP_DECL_CONSSEPASOL((*conssepasol)), int sepafreq, int sepapriority, SCIP_Bool delaysepa)
Definition: scip_cons.c:219
public data structures and miscellaneous methods
static SCIP_RETCODE lifting(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Real xval, SCIP_Real yval, SCIP_Real xlb, SCIP_Real xub, SCIP_Real ylb, SCIP_Real yub, int min_max, SCIP_Real cutcoeff[4], SCIP_Real *convenvvalue, SCIP_Bool *success)
Definition: cons_bivariate.c:3510
SCIP_RETCODE SCIPunlockVarCons(SCIP *scip, SCIP_VAR *var, SCIP_CONS *cons, SCIP_Bool lockdown, SCIP_Bool lockup)
Definition: scip_var.c:4376
Definition: type_expr.h:85
SCIP_EXPORT SCIP_RETCODE SCIPexprintEval(SCIP_EXPRINT *exprint, SCIP_EXPRTREE *tree, SCIP_Real *varvals, SCIP_Real *val)
Definition: exprinterpret_cppad.cpp:2295
SCIP_RETCODE SCIPdropVarEvent(SCIP *scip, SCIP_VAR *var, SCIP_EVENTTYPE eventtype, SCIP_EVENTHDLR *eventhdlr, SCIP_EVENTDATA *eventdata, int filterpos)
Definition: scip_event.c:390
Definition: type_expr.h:39
SCIP_Bool SCIPisSumLT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:683
void SCIPexprgraphSetVarNodeLb(SCIP_EXPRGRAPH *exprgraph, SCIP_EXPRGRAPHNODE *varnode, SCIP_Real lb)
Definition: expr.c:15044
SCIP_RETCODE SCIPsetConshdlrCopy(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSHDLRCOPY((*conshdlrcopy)), SCIP_DECL_CONSCOPY((*conscopy)))
Definition: scip_cons.c:331
static SCIP_Bool isConvexLocal(SCIP *scip, SCIP_CONS *cons, SCIP_SIDETYPE side)
Definition: cons_bivariate.c:4523
SCIP_RETCODE SCIPexprtreeSetVars(SCIP_EXPRTREE *tree, int nvars, SCIP_VAR **vars)
Definition: nlp.c:112
SCIP_RETCODE SCIPprintCons(SCIP *scip, SCIP_CONS *cons, FILE *file)
Definition: scip_cons.c:2472
SCIP_EXPRINTDATA * SCIPexprtreeGetInterpreterData(SCIP_EXPRTREE *tree)
Definition: expr.c:8658
constraint handler for nonlinear constraints
static SCIP_DECL_CONSDISABLE(consDisableBivariate)
Definition: cons_bivariate.c:7226
SCIP_CONSHDLRDATA * SCIPconshdlrGetData(SCIP_CONSHDLR *conshdlr)
Definition: cons.c:4211
SCIP_RETCODE SCIPcreateLPSol(SCIP *scip, SCIP_SOL **sol, SCIP_HEUR *heur)
Definition: scip_sol.c:361
SCIP_Bool SCIPisCutApplicable(SCIP *scip, SCIP_ROW *cut)
Definition: scip_cut.c:177
Definition: struct_lp.h:192
SCIP_RETCODE SCIPcreateVar(SCIP *scip, SCIP_VAR **var, const char *name, SCIP_Real lb, SCIP_Real ub, SCIP_Real obj, SCIP_VARTYPE vartype, SCIP_Bool initial, SCIP_Bool removable, SCIP_DECL_VARDELORIG((*vardelorig)), SCIP_DECL_VARTRANS((*vartrans)), SCIP_DECL_VARDELTRANS((*vardeltrans)), SCIP_DECL_VARCOPY((*varcopy)), SCIP_VARDATA *vardata)
Definition: scip_var.c:104
methods for debugging
SCIP_RETCODE SCIPcreateEmptyRowCons(SCIP *scip, SCIP_ROW **row, SCIP_CONSHDLR *conshdlr, const char *name, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool removable)
Definition: scip_lp.c:1268
public methods for LP management
void SCIPexprgraphSetVarNodeUb(SCIP_EXPRGRAPH *exprgraph, SCIP_EXPRGRAPHNODE *varnode, SCIP_Real ub)
Definition: expr.c:15064
Definition: cons_quadratic.h:121
SCIP_RETCODE SCIPexprCreate(BMS_BLKMEM *blkmem, SCIP_EXPR **expr, SCIP_EXPROP op,...)
Definition: expr.c:5974
public methods for cuts and aggregation rows
SCIP_RETCODE SCIPincludeConshdlrBivariate(SCIP *scip)
Definition: cons_bivariate.c:7850
Definition: type_set.h:41
static SCIP_RETCODE removeFixedVariables(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS *cons, SCIP_Bool *ischanged, SCIP_Bool *isupgraded)
Definition: cons_bivariate.c:475
Definition: struct_expr.h:116
static SCIP_DECL_CONSEXITSOL(consExitsolBivariate)
Definition: cons_bivariate.c:6422
Definition: type_var.h:45
void SCIPintervalAdd(SCIP_Real infinity, SCIP_INTERVAL *resultant, SCIP_INTERVAL operand1, SCIP_INTERVAL operand2)
Definition: intervalarith.c:578
SCIP_EXPORT SCIP_Real SCIPnodeGetEstimate(SCIP_NODE *node)
Definition: tree.c:7377
void SCIPexprgraphDisableNode(SCIP_EXPRGRAPH *exprgraph, SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:14581
SCIP_Real SCIPintervalGetSup(SCIP_INTERVAL interval)
Definition: intervalarith.c:360
SCIP_Bool SCIPintervalAreDisjoint(SCIP_INTERVAL operand1, SCIP_INTERVAL operand2)
Definition: intervalarith.c:475
static SCIP_DECL_CONSINITPRE(consInitpreBivariate)
Definition: cons_bivariate.c:6215
Definition: type_set.h:45
constraint handler for bivariate nonlinear constraints
Definition: struct_expr.h:89
SCIP_Bool SCIPisFeasGE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:823
SCIP_EXPORT SCIP_RETCODE SCIPexprintHessianDense(SCIP_EXPRINT *exprint, SCIP_EXPRTREE *tree, SCIP_Real *varvals, SCIP_Bool new_varvals, SCIP_Real *val, SCIP_Real *hessian)
Definition: exprinterpret_cppad.cpp:2599
SCIP_Real SCIPexprGetMonomialCoef(SCIP_EXPRDATA_MONOMIAL *monomial)
Definition: expr.c:5901
SCIP_RETCODE SCIPincludeEventhdlrBasic(SCIP *scip, SCIP_EVENTHDLR **eventhdlrptr, const char *name, const char *desc, SCIP_DECL_EVENTEXEC((*eventexec)), SCIP_EVENTHDLRDATA *eventhdlrdata)
Definition: scip_event.c:94
SCIP_RETCODE SCIPaddRealParam(SCIP *scip, const char *name, const char *desc, SCIP_Real *valueptr, SCIP_Bool isadvanced, SCIP_Real defaultvalue, SCIP_Real minvalue, SCIP_Real maxvalue, SCIP_DECL_PARAMCHGD((*paramchgd)), SCIP_PARAMDATA *paramdata)
Definition: scip_param.c:129
SCIP_RETCODE SCIPunmarkConsPropagate(SCIP *scip, SCIP_CONS *cons)
Definition: scip_cons.c:1978
void * SCIPexprgraphGetNodeVar(SCIP_EXPRGRAPH *exprgraph, SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13066
public methods for the LP relaxation, rows and columns
SCIP_Bool SCIPisConcaveQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:15080
static SCIP_DECL_CONSSEPASOL(consSepasolBivariate)
Definition: cons_bivariate.c:6767
SCIP_EXPORT int SCIPvarGetNLocksDownType(SCIP_VAR *var, SCIP_LOCKTYPE locktype)
Definition: var.c:3184
public methods for nonlinear relaxations
SCIP_RETCODE SCIPaddLinearVarQuadratic(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, SCIP_Real coef)
Definition: cons_quadratic.c:14604
Definition: type_set.h:39
SCIP_RETCODE SCIPgetSolVals(SCIP *scip, SCIP_SOL *sol, int nvars, SCIP_VAR **vars, SCIP_Real *vals)
Definition: scip_sol.c:1389
Definition: cons_bivariate.h:76
public methods for branching rule plugins and branching
SCIP_RETCODE SCIPaddRow(SCIP *scip, SCIP_ROW *row, SCIP_Bool forcecut, SCIP_Bool *infeasible)
Definition: scip_cut.c:220
public methods for managing events
general public methods
SCIP_Bool SCIPisFeasGT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:810
SCIP_RETCODE SCIPincludeNonlinconsUpgrade(SCIP *scip, SCIP_DECL_NONLINCONSUPGD((*nonlinconsupgd)), SCIP_DECL_EXPRGRAPHNODEREFORM((*nodereform)), int priority, SCIP_Bool active, const char *conshdlrname)
Definition: cons_nonlinear.c:9278
public methods for solutions
SCIP_RETCODE SCIPchgRowRhs(SCIP *scip, SCIP_ROW *row, SCIP_Real rhs)
Definition: scip_lp.c:1451
SCIP_RETCODE SCIPchgRowLhs(SCIP *scip, SCIP_ROW *row, SCIP_Real lhs)
Definition: scip_lp.c:1427
static SCIP_DECL_CONSINITLP(consInitlpBivariate)
Definition: cons_bivariate.c:6522
SCIP_RETCODE SCIPdropEvent(SCIP *scip, SCIP_EVENTTYPE eventtype, SCIP_EVENTHDLR *eventhdlr, SCIP_EVENTDATA *eventdata, int filterpos)
Definition: scip_event.c:310
int SCIPgetNLinearVarsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:14860
Definition: type_expr.h:86
public methods for the probing mode
SCIP_Bool SCIPisFeasLT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:784
SCIP_RETCODE SCIPsetConshdlrDeactive(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSDEACTIVE((*consdeactive)))
Definition: scip_cons.c:677
SCIP_RETCODE SCIPaddVarToRow(SCIP *scip, SCIP_ROW *row, SCIP_VAR *var, SCIP_Real val)
Definition: scip_lp.c:1539
static SCIP_DECL_CONSGETVARS(consGetVarsBivariate)
Definition: cons_bivariate.c:7385
SCIP_CONS ** SCIPconshdlrGetConss(SCIP_CONSHDLR *conshdlr)
Definition: cons.c:4563
int SCIPgetNBilinTermsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:14962
public methods for message output
NLP local search primal heuristic using sub-SCIPs.
SCIP_Real SCIPgetSolTransObj(SCIP *scip, SCIP_SOL *sol)
Definition: scip_sol.c:1482
SCIP_RETCODE SCIPexprgraphReleaseNode(SCIP_EXPRGRAPH *exprgraph, SCIP_EXPRGRAPHNODE **node)
Definition: expr.c:14435
Definition: type_var.h:84
SCIP_RETCODE SCIPaddIntParam(SCIP *scip, const char *name, const char *desc, int *valueptr, SCIP_Bool isadvanced, int defaultvalue, int minvalue, int maxvalue, SCIP_DECL_PARAMCHGD((*paramchgd)), SCIP_PARAMDATA *paramdata)
Definition: scip_param.c:73
static SCIP_RETCODE generateEstimatingHyperplane(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Bool doover, SCIP_Real *x0y0, SCIP_Real *coefx, SCIP_Real *coefy, SCIP_Real *constant, SCIP_Bool *success)
Definition: cons_bivariate.c:1527
static SCIP_RETCODE generateOrthogonal_lx_uy_Underestimator(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Real *xyref, SCIP_Real cutcoeff[4], SCIP_Real *convenvvalue, SCIP_Bool *success)
Definition: cons_bivariate.c:2450
static SCIP_RETCODE generateConvexConcaveUnderestimator(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_EXPRTREE *f_yfixed, SCIP_EXPRTREE *vred, SCIP_Real xyref[2], SCIP_Real cutcoeff[4], SCIP_Real *convenvvalue, SCIP_Bool *success)
Definition: cons_bivariate.c:2830
static SCIP_RETCODE propagateBoundsTightenVar(SCIP *scip, SCIP_VAR *var, SCIP_INTERVAL bounds, SCIP_CONS *cons, SCIP_RESULT *result, int *nchgbds)
Definition: cons_bivariate.c:5111
static SCIP_RETCODE generate1ConvexIndefiniteUnderestimatorInTheInteriorPatternB(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Real xyref[2], SCIP_Real cutcoeff[4], SCIP_Real *convenvvalue, SCIP_Bool *success)
Definition: cons_bivariate.c:3989
void SCIPintervalMulScalar(SCIP_Real infinity, SCIP_INTERVAL *resultant, SCIP_INTERVAL operand1, SCIP_Real operand2)
Definition: intervalarith.c:1003
Definition: type_lp.h:56
Definition: struct_nlp.h:63
SCIP_Real SCIPgetRhsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:15000
SCIP_EXPORT SCIP_RETCODE SCIPexprintHessianSparsityDense(SCIP_EXPRINT *exprint, SCIP_EXPRTREE *tree, SCIP_Real *varvals, SCIP_Bool *sparsity)
Definition: exprinterpret_cppad.cpp:2526
public methods for message handling
SCIP_Bool SCIPisGT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:475
SCIP_EXPRGRAPHNODE ** SCIPexprgraphGetNodeChildren(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:12984
SCIP_Real SCIPgetRowLPFeasibility(SCIP *scip, SCIP_ROW *row)
Definition: scip_lp.c:1848
SCIP_Real * SCIPexprGetMonomialExponents(SCIP_EXPRDATA_MONOMIAL *monomial)
Definition: expr.c:5931
SCIP_RETCODE SCIPexprtreeSubstituteVars(SCIP_EXPRTREE *tree, SCIP_EXPR **substexprs)
Definition: expr.c:9046
Definition: type_retcode.h:45
static SCIP_DECL_CONSENABLE(consEnableBivariate)
Definition: cons_bivariate.c:7194
Definition: type_expr.h:75
static SCIP_RETCODE generate1ConvexIndefiniteUnderestimatorInTheInteriorPatternA(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Real xyref[2], SCIP_Real cutcoeff[4], SCIP_Real *convenvvalue, SCIP_Bool *success)
Definition: cons_bivariate.c:3794
Definition: type_set.h:44
SCIP_RETCODE SCIPgetProbvarSum(SCIP *scip, SCIP_VAR **var, SCIP_Real *scalar, SCIP_Real *constant)
Definition: scip_var.c:1796
Definition: struct_expr.h:155
SCIP_RETCODE SCIPcatchVarEvent(SCIP *scip, SCIP_VAR *var, SCIP_EVENTTYPE eventtype, SCIP_EVENTHDLR *eventhdlr, SCIP_EVENTDATA *eventdata, int *filterpos)
Definition: scip_event.c:344
static SCIP_RETCODE generateCut(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_CONS *cons, SCIP_SOL *sol, SCIP_SIDETYPE violside, SCIP_Real cutmaxrange, SCIP_ROW **row)
Definition: cons_bivariate.c:4321
SCIP_RETCODE SCIPevalExprtreeLocalBounds(SCIP *scip, SCIP_EXPRTREE *tree, SCIP_Real infinity, SCIP_INTERVAL *val)
Definition: scip_expr.c:233
void SCIPintervalSub(SCIP_Real infinity, SCIP_INTERVAL *resultant, SCIP_INTERVAL operand1, SCIP_INTERVAL operand2)
Definition: intervalarith.c:685
Definition: type_result.h:45
static SCIP_RETCODE enforceViolatedFixedNonlinear(SCIP *scip, SCIP_CONS **conss, int nconss, SCIP_Bool *reduceddom, SCIP_Bool *infeasible)
Definition: cons_bivariate.c:4984
SCIP_Real * SCIPgetCoefsLinearVarsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:14888
SCIP_VAR * SCIPgetLinearVarBivariate(SCIP *scip, SCIP_CONS *cons)
Definition: cons_bivariate.c:8058
Definition: type_result.h:46
static SCIP_RETCODE generateLinearizationCut(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_CONS *cons, SCIP_Real *x0y0, SCIP_Bool newxy, SCIP_ROW **row)
Definition: cons_bivariate.c:1451
Definition: struct_expr.h:55
static SCIP_RETCODE generate1ConvexIndefiniteUnderestimator(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_CONS *cons, SCIP_Real *xyref, SCIP_ROW **row)
Definition: cons_bivariate.c:4176
SCIP_RETCODE SCIPcreateConsQuadratic(SCIP *scip, SCIP_CONS **cons, const char *name, int nlinvars, SCIP_VAR **linvars, SCIP_Real *lincoefs, int nquadterms, SCIP_VAR **quadvars1, SCIP_VAR **quadvars2, SCIP_Real *quadcoefs, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable)
Definition: cons_quadratic.c:14269
SCIP_Bool SCIPconsIsMarkedPropagate(SCIP_CONS *cons)
Definition: cons.c:8285
public methods for primal heuristics
SCIP_RETCODE SCIPaddVarsToRow(SCIP *scip, SCIP_ROW *row, int nvars, SCIP_VAR **vars, SCIP_Real *vals)
Definition: scip_lp.c:1565
void SCIPinfoMessage(SCIP *scip, FILE *file, const char *formatstr,...)
Definition: scip_message.c:198
SCIP_RETCODE SCIPcreateRowCons(SCIP *scip, SCIP_ROW **row, SCIP_CONSHDLR *conshdlr, const char *name, int len, SCIP_COL **cols, SCIP_Real *vals, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool removable)
Definition: scip_lp.c:1136
Definition: type_retcode.h:43
SCIP_RETCODE SCIPreleaseCons(SCIP *scip, SCIP_CONS **cons)
Definition: scip_cons.c:1109
SCIP_RETCODE SCIPexprCreateLinear(BMS_BLKMEM *blkmem, SCIP_EXPR **expr, int nchildren, SCIP_EXPR **children, SCIP_Real *coefs, SCIP_Real constant)
Definition: expr.c:6503
static SCIP_RETCODE generateUnderestimatorParallelYFacets(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Real *xyref, SCIP_Real cutcoeff[4], SCIP_Real *convenvvalue, SCIP_Bool *success)
Definition: cons_bivariate.c:1825
Definition: objbenders.h:33
SCIP_RETCODE SCIPsetConshdlrProp(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSPROP((*consprop)), int propfreq, SCIP_Bool delayprop, SCIP_PROPTIMING proptiming)
Definition: scip_cons.c:265
public methods for global and local (sub)problems
void SCIPmarkRowNotRemovableLocal(SCIP *scip, SCIP_ROW *row)
Definition: scip_lp.c:1706
Definition: type_var.h:43
static SCIP_RETCODE initSepaDataCreateVred(SCIP *scip, SCIP_EXPRTREE **vred, SCIP_EXPRTREE *f)
Definition: cons_bivariate.c:960
SCIP_Real SCIPadjustedVarLb(SCIP *scip, SCIP_VAR *var, SCIP_Real lb)
Definition: scip_var.c:4551
SCIP_RETCODE SCIPexprtreeSetParams(SCIP_EXPRTREE *tree, int nparams, SCIP_Real *paramvals)
Definition: expr.c:8877
SCIP_RETCODE SCIPsetConshdlrEnable(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSENABLE((*consenable)))
Definition: scip_cons.c:700
static void perturb(SCIP_Real *val, SCIP_Real lb, SCIP_Real ub, SCIP_Real amount)
Definition: cons_bivariate.c:1265
#define SCIPduplicateBlockMemory(scip, ptr, source)
Definition: scip_mem.h:90
static SCIP_DECL_CONSEXITPRE(consExitpreBivariate)
Definition: cons_bivariate.c:6241
Definition: exprinterpret_cppad.cpp:308
Definition: type_result.h:39
Definition: struct_event.h:186
SCIP_RETCODE SCIPsetConshdlrInitlp(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSINITLP((*consinitlp)))
Definition: scip_cons.c:608
SCIP_Bool SCIPintervalIsSubsetEQ(SCIP_Real infinity, SCIP_INTERVAL operand1, SCIP_INTERVAL operand2)
Definition: intervalarith.c:456
SCIP_EXPORT SCIP_RETCODE SCIPexprintCompile(SCIP_EXPRINT *exprint, SCIP_EXPRTREE *tree)
Definition: exprinterpret_cppad.cpp:2187
SCIP_RETCODE SCIPexprtreeEval(SCIP_EXPRTREE *tree, SCIP_Real *varvals, SCIP_Real *val)
Definition: expr.c:8724
Definition: cons_bivariate.h:78
Definition: type_expr.h:48
SCIP_RETCODE SCIPsetConsChecked(SCIP *scip, SCIP_CONS *cons, SCIP_Bool check)
Definition: scip_cons.c:1282
Definition: type_expr.h:41
void SCIPexprgraphEnableNode(SCIP_EXPRGRAPH *exprgraph, SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:14554
memory allocation routines
SCIP_RETCODE SCIPcomputeHyperplaneThreePoints(SCIP *scip, SCIP_Real a1, SCIP_Real a2, SCIP_Real a3, SCIP_Real b1, SCIP_Real b2, SCIP_Real b3, SCIP_Real c1, SCIP_Real c2, SCIP_Real c3, SCIP_Real *alpha, SCIP_Real *beta, SCIP_Real *gamma_, SCIP_Real *delta)
Definition: cons_nonlinear.c:10001
Definition: type_var.h:58