> Now my question is: should I solve the model from scratch in the case > I have to remove a lot of variables?
Generally, not. > Or is there a parameter configuration I should use in my specific > case? > Glp_simplex always starts the search from the current basis which is provided in glp_prob by means of the statuses of rows and columns. This allows to continue the search (re-optimize) efficiently if you obtain an optimal basis, change the lp, and then call glp_simplex once again. However, in this case you need to make sure that the row/column statuses define a "correct" basis--the number of basic auxiliary/structural variables should be equal to the number of rows, and the basis matrix consisting of columns of basic variables, including unity ones for auxiliary variables, should be non-singular. For example, removing an active (more precisely, binding) constraint, i.e. a non-basic row, makes the basis incorrect. To avoid this you may either remove the row "logically" by making it free (unbounded) rather to remove it "physically", or make the row basic (non-binding) before removing it by changing the row/column statuses in an appropriate way. _______________________________________________ Help-glpk mailing list Help-glpk@gnu.org https://lists.gnu.org/mailman/listinfo/help-glpk
