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problem.strongbranchcb

problem.strongbranchcb

Purpose
Performs strong branching iterations on all specified bound changes. For each candidate bound change, strongbranchcb performs dual simplex iterations starting from the current optimal solution of the base LP, and returns both the status and objective value reached after these iterations.
Synopsis

problem.strongbranchcb (bndind, bndtype, bndval, itrlimit, objval, status, sbsolvecb, vContext)

ret = sbsolvecb (prob, vContext, ibnd)
Arguments
bndind 
Array containing the columns (i.e. xpress.var objects, indices, or names) on which the bounds will change.
bndtype 
Character array indicating the type of bound to change:
U 
indicates change the upper bound;
L 
indicates change the lower bound;
B 
indicates change both bounds, i.e. fix the column.
bndval 
Array giving the new bound values.
itrlimit 
Maximum number of LP iterations to perform for each bound change.
objval 
Objective value of each LP after performing the strong branching iterations.
status 
Status of each LP after performing the strong branching iterations, as detailed for the LPSTATUS attribute.
sbsolvecb 
Function to be called after each strong branch has been reoptimized.
vContext 
User context to be provided for sbsolvecb.
ibnd 
The index of bound for which sbsolvecb is called.
Further information

Prior to calling strongbranchcb, the current LP problem must have been solved to optimality and an optimal basis must be available.

strongbranchcb is an extension to problem.strongbranch. If identical input arguments are provided both will return identical results, the difference being that for the case of PRSstrongbranchcb the sbnodecb function is called at the end of each LP reoptimization.

For each branch optimized, the LP can be interrogated: the LP status of the branch is available through checking LPSTATUS, and the objective function value is available through LPOBJVAL. It is possible to access the full current LP solution by using problem.getlpsol.



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