Hello David, have a look at the "Big M method". Take care to choose M as small as possible.
Best regards Heinrich Schuchardt On 27.07.2016 22:21, usa usa wrote: > Hi, > > I am trying to build a MILP. > > I need to set the number of linear constraints in the model as a > decision variable. > > For example: > > max 8* x1 + 6 * x2 - x3 > s.t. > constraint 1 : x1 + x2 <= 29 > constraint 2 : x1 - x2 <= 5 > constraint 3 : x2 + x3 <= 56 > > I would like to make the all three constraints as candidates such that > > 1. the objective maximized. > 2. At least one constraint must be active > 3. How many of candidate constraints are active depends on the objective > optimization value. > > I know this may have exponential complexity because for 3 candidates, I > can have 2^3 = 8 combinations of constraints. > > Are there some ways to out all candidate in the model and solve it for > one run to get the optimal solution and let the model decide which > candidates should be active / > > thanks > > David > > > > > > _______________________________________________ > Help-glpk mailing list > [email protected] > https://lists.gnu.org/mailman/listinfo/help-glpk > _______________________________________________ Help-glpk mailing list [email protected] https://lists.gnu.org/mailman/listinfo/help-glpk
