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type_pricer.h File Reference ## Detailed Descriptiontype definitions for variable pricers Definition in file type_pricer.h. Go to the source code of this file.
## Macro Definition Documentation
copy method for pricer plugins (called when SCIP copies plugins) input: - scip : SCIP main data structure
- pricer : the variable pricer itself
- valid : was the copying process valid?
Definition at line 46 of file type_pricer.h.
destructor of variable pricer to free user data (called when SCIP is exiting) input: - scip : SCIP main data structure
- pricer : the variable pricer itself
Definition at line 54 of file type_pricer.h.
initialization method of variable pricer (called after problem was transformed and pricer is active) input: - scip : SCIP main data structure
- pricer : the variable pricer itself
Definition at line 62 of file type_pricer.h.
deinitialization method of variable pricer (called before transformed problem is freed and pricer is active) input: - scip : SCIP main data structure
- pricer : the variable pricer itself
Definition at line 70 of file type_pricer.h.
solving process initialization method of variable pricer (called when branch and bound process is about to begin) This method is called when the presolving was finished and the branch and bound process is about to begin. The variable pricer may use this call to initialize its branch and bound specific data. input: - scip : SCIP main data structure
- pricer : the variable pricer itself
Definition at line 81 of file type_pricer.h.
solving process deinitialization method of variable pricer (called before branch and bound process data is freed) This method is called before the branch and bound process is freed. The variable pricer should use this call to clean up its branch and bound data. input: - scip : SCIP main data structure
- pricer : the variable pricer itself
Definition at line 92 of file type_pricer.h.
reduced cost pricing method of variable pricer for feasible LPs Searches for variables that can contribute to improve the current LP's solution value. In standard branch-and-price, these are variables with negative dual feasibility, that is negative reduced costs for non-negative variables, positive reduced costs for non-positive variables, and non-zero reduced costs for variables that can be negative and positive. The method is called in the LP solving loop after an LP was proven to be feasible. Whenever the pricer finds a variable with negative dual feasibility, it should call SCIPcreateVar() and SCIPaddPricedVar() to add the variable to the problem. Furthermore, it should call the appropriate methods of the constraint handlers to add the necessary variable entries to the constraints. In the usual case that the pricer either adds a new variable or ensures that there are no further variables with negative dual feasibility, the result pointer should be set to SCIP_SUCCESS. Only if the pricer aborts pricing without creating a new variable, but there might exist additional variables with negative dual feasibility, the result pointer should be set to SCIP_DIDNOTRUN. In this case, which sometimes is referred to as "early branching", the lp solution will not be used as a lower bound. The pricer can, however, store a valid lower bound in the lowerbound pointer. If you use your own branching rule (e.g., to branch on constraints), make sure that it is able to branch on pseudo solutions. Otherwise, SCIP will use its default branching rules (which all branch on variables). This could disturb the pricing problem or branching might not even be possible, e.g., if all yet created variables have already been fixed. input: - scip : SCIP main data structure
- pricer : the variable pricer itself
- lowerbound : pointer to store a lower bound found by the pricer
- stopearly : should pricing be stopped, although new variables were added? (doing early branching)
- result : pointer to store the result of the pricer call
possible return values for *result: - SCIP_SUCCESS : at least one improving variable was found, or it is ensured that no such variable exists
- SCIP_DIDNOTRUN : the pricing process was aborted by the pricer, there is no guarantee that the current LP solution is optimal
Definition at line 130 of file type_pricer.h.
Farkas pricing method of variable pricer for infeasible LPs Searches for variables that can contribute to the feasibility of the current LP. In standard branch-and-price, these are variables with positive Farkas values: The LP was proven infeasible, so we have an infeasibility proof by the dual Farkas multipliers y. With the values of y, an implicit inequality y^T A x >= y^T b is associated, with b given by the sides of the LP rows and the sign of y: - if y_i is positive, b_i is the left hand side of the row,
- if y_i is negative, b_i is the right hand side of the row.
y is chosen in a way, such that the valid inequality y^T A x >= y^T b is violated by all x, especially by the (for this inequality least infeasible solution) x' defined by x'_i := ub_i, if y^T A_i >= 0 x'_i := lb_i, if y^T A_i < 0. Pricing in this case means to add variables i with positive Farkas value, i.e. y^T A_i x'_i > 0. The method is called in the LP solving loop after an LP was proven to be infeasible. Whenever the pricer finds a variable with positive Farkas value, it should call SCIPcreateVar() and SCIPaddPricedVar() to add the variable to the problem. Furthermore, it should call the appropriate methods of the constraint handlers to add the necessary variable entries to the constraints. input: - scip : SCIP main data structure
- pricer : the variable pricer itself
Definition at line 159 of file type_pricer.h. ## Typedef Documentation
variable pricer data Definition at line 35 of file type_pricer.h.
locally defined variable pricer data Definition at line 36 of file type_pricer.h. |