> I print out the solution of my problem and it is like the following > No. Column name St Activity Lower bound Upper bound Marginal > ------ ------------ -- ------------- ------------- ------------- > ------------- > 1 z[0][0] B 0 0 1 > 2 z[0][1] NL 0 0 1 > eps > 3 z[0][2] B 0.25 0 1 > 4 z[0][3] B 0.75 0 1 > 5 z[1][0] NU 1 0 1 > eps > 6 z[1][1] B 0 0 1 > 7 z[1][2] NL 0 0 1 > eps > ............. > I have a couple of questions regarding the result. > 1. What does columns St and Marginal mean?
"St" is the status of auxiliary/structural variable in the basic solution found: B means "basic", NL means "non-basic, lower bound is active", NU means "non-basic, upper bound is active". "Marginal" is the reduced cost of auxiliary/structural variable. > 2. Activity is the value of the column variable in the optimal solution, > right? Yes. > But I have set the column kind to be binary variable by > glp_set_col_kind(lp,Col_Num,GLP_BV); How can the variables take 0.25 and > 0.75 in the optimal solution? The solution you obtained is a basic optimal solution to LP relaxation of your instance. To obtain an integer optimal solution you should call glp_intopt immediately after glp_simplex, and then use glp_print_mip rather than glp_print_sol. _______________________________________________ Help-glpk mailing list [email protected] http://lists.gnu.org/mailman/listinfo/help-glpk
