I've been looking everywhere, and I can't seem to find any information on whether GLPK can do successive optimizations on the same model, on which we add a constraint at each iteration.More concretely, I want to implement a Branch and Bound algorithm on a 01ILP, so at each iteration, I'll fix a variable either to 0 or 1 (depending on the branch) and solve the relaxed LP, but I don't want to reoptimize from scratch each time.
Do you know if such a thing is possible using GLPK (and Julia/JuMP as modeling language)? And if not, do you see a solver that would do that?
