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Forum migration: please go to the Data Science community

The Decision Optimization group in the Data Science community is now live! Please join us there! Only the content from more than 4 months ago was migrated so far, but the newer content follows. This forum will very soon be turned read-only, and will disappear shortly after the migration...



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Re: Different optimal solution for same data set from MIP and CP

Originally posted by: memop Thank you PaulRubin. I will try your suggestion. Regards.

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Re: Different optimal solution for same data set from MIP and CP

As Daniel suggested, take the solution from the CP model and fix the variables in the MIP model to those values (by setting lower bound = upper bound = value in CP solution). Then try to solve the MIP model. CPLEX should say it is infeasible. Assuming so, use the conflict refiner to identify a...

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Re: Different optimal solution for same data set from MIP and CP

Originally posted by: memop Thank you Daniel. The MIP model is established properly, is it true? The problem stems from the CP model. But when I checked the results obtained from CP model, all the constraints are satisfied and all assignments are proper. Where exactly should we look for...

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Re: Different optimal solution for same data set from MIP and CP

You CP model gives an objective value of 55. For your MIP model already the initial LP relaxation gives a lower bound of 56.8, proving that this model cannot have an optimal solution of 55. To debug this I suggest to take the solution found from CP and figure out why it is infeasible in MIP.


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Different optimal solution for same data set from MIP and CP

Originally posted by: memop Hi, I have modeled my problem by using CPLEX (MIP Model) and CP (CP Model). My models consist of some logical constraints. So the MIP model has been established with indicator constraints. The models run and all constraints are satisfied in two models....

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Re: Logical Constraint Modelling

Originally posted by: memop Dear Alex, I have modeled my problem by using CPLEX (MIP Model) and CP (CP Model). The models run and all constraints are satisfied in two models. But both models produce different optimum solutions for the same data set. The models are attached to the post. Do...

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