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user_compare_candidates

int user_compare_candidates(void *user, branch_obj *can1, branch_obj *can2,
                            int *which_is_better)

Description:

By the time this function is invoked, the children of the current search tree node corresponding to each branching candidate have been pre-solved, i.e., the objval, termcode, iterd, and feasible fields of the can1 and can2 structures are filled out. Note that if the termination code for a child is D_UNBOUNDED or D_OBJLIM, i.e., the dual problem is unbounded or the objective limit is reached, then the objective value of that child is set to MAXDOUBLE / 2. Similarly, if the termination code is one of D_ITLIM (iteration limit reached), D_INFEASIBLE (dual infeasible) or ABANDONED (because of numerical difficulties) then the objective value of that child is set to that of the parent's.

Based on this information the user must choose which candidate he considers better and whether to branch on this better one immediately without checking the remaining candidates. As such, there are four possible answers: FIRST_CANDIDATE_BETTER, SECOND_CANDIDATE_BETTER, FIRST_CANDIDATE_BETTER_AND_BRANCH_ON_IT and SECOND_CANDIDATE_BETTER_AND_BRANCH_ON_IT. An answer ending with _AND_BRANCH_ON_IT indicates that the user wants to terminate the strong branching process and select that particular candidate for branching.

There are several default options. In each of them, objective values of the pre-solved LP relaxations are compared.

Arguments:

void *user	IN	Pointer to the user-defined LP data structure.
branch_obj *can1	IN	One of the candidates to be compared.
branch_obj *can2	IN	The other candidate to be compared.
int *which_is_better	OUT	The user's choice. See the description above.

Return values:

ERROR	Error. DEFAULT is used.
USER_NO_PP	User filled out *which_is_better.
DEFAULT	Regulated by the compare_candidates_default parameter, initially set to LOWEST_LOW_OBJ unless over-ridden by the user.
BIGGEST_DIFFERENCE	Prefer the candidate with the biggest difference between highest and lowest objective function values.
LOWEST_LOW	Prefer the candidate with the lowest minimum objective function value. The minimum is taken over the objective function values of all the children.
HIGHEST_LOW	Prefer the candidate with the highest minimum objective function value.
LOWEST_HIGH	Prefer the candidate with the lowest maximum objective function value.
HIGHEST_HIGH	Prefer the candidate with the highest maximum objective function value .

Wrapper invoked from:

select_branching_object() after the LP relaxations of the children have been pre-solved.