Hi, everyone.
I am using Cplex 12.4 to solve my MIP model with minimization objective. The optimal solution is 203.
I then add several constraints to the model (they acutally indicate values for some decision variables), and the optimal solution is 200.
It seems impossible theoritically, but Cplex solved both models to optimality without reporting error. I am confused...
I have uploaded log files of these two runs. Thanks for your help!
Topic

Re: Adding constraints improves the optimal solution?
20130129T22:50:39ZThis is the accepted answer. This is the accepted answer.If you add the number of columns eliminated by presolve and the number of columns in the reduced MIP, you get 12,222 in the first model and 12,230 in the second model. In the process of adding constraints, did you also add variables? That could explain the improved objective value.
Paul
Mathematicians are like Frenchmen: whenever you say something to them, they translate it into their own language, and at once it is something entirely different. (Goethe) 
Re: Adding constraints improves the optimal solution?
20130130T01:12:13ZThis is the accepted answer. This is the accepted answer. SystemAdmin
 20130129T22:50:39Z
If you add the number of columns eliminated by presolve and the number of columns in the reduced MIP, you get 12,222 in the first model and 12,230 in the second model. In the process of adding constraints, did you also add variables? That could explain the improved objective value.
Paul
Mathematicians are like Frenchmen: whenever you say something to them, they translate it into their own language, and at once it is something entirely different. (Goethe)
In the added constraints, I just specify the values for some existing variables in the first model. I didn't introduce new variables
Could this difference between 12,222 and 12,230 caused by the "substitutions" did by "Aggregator"?
Besides, I am not sure, but shouldn't adding variables also degrade the objective value? 
Re: Adding constraints improves the optimal solution?
20130130T01:59:17ZThis is the accepted answer. This is the accepted answer. SystemAdmin
 20130129T22:50:39Z
If you add the number of columns eliminated by presolve and the number of columns in the reduced MIP, you get 12,222 in the first model and 12,230 in the second model. In the process of adding constraints, did you also add variables? That could explain the improved objective value.
Paul
Mathematicians are like Frenchmen: whenever you say something to them, they translate it into their own language, and at once it is something entirely different. (Goethe)
Thanks again for your help!Attachments

Re: Adding constraints improves the optimal solution?
20130130T03:14:52ZThis is the accepted answer. This is the accepted answer. xhan
 20130130T01:12:13Z
Thank you, Paul!
In the added constraints, I just specify the values for some existing variables in the first model. I didn't introduce new variables
Could this difference between 12,222 and 12,230 caused by the "substitutions" did by "Aggregator"?
Besides, I am not sure, but shouldn't adding variables also degrade the objective value?
Paul
Mathematicians are like Frenchmen: whenever you say something to them, they translate it into their own language, and at once it is something entirely different. (Goethe)