For max=1, there is no solution but for max=2 it has solution. How can we find upper bound of max using loop for similar problem?
p = MixedIntegerLinearProgram(solver='GLPK') x = p.new_variable() p.set_binary(x) p.set_objective(x[0] ) p.add_constraint(x[0]+x[1],max=1) p.add_constraint(x[0],min=1) p.add_constraint(x[1],min=1) print p.show() print p.solve() A=p.get_values(x) print A On Mon, Jul 6, 2020 at 11:06 PM chandra chowdhury <pc.chandr...@gmail.com> wrote: > Hi, > I am trying to solve MILP using Sage. Problem is if there is no solution > it gives an error. Instead of an error, I want to change constraints > (like if initial max=100 which does not give solution, new max=101 which > may give solution) > and run the solver automatically. > > p = MixedIntegerLinearProgram(solver='GLPK') > .... > p.solve() > > sage.numerical.mip.MIPSolverException: GLPK: Problem has no feasible > solution > > -- You received this message because you are subscribed to the Google Groups "sage-support" group. To unsubscribe from this group and stop receiving emails from it, send an email to sage-support+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/sage-support/CAC3pSBLinEG_4tubDWocwmjRfgw4nCRjo_pqgXaOrLdxqt8qrg%40mail.gmail.com.
