Decision Optimization

Decision Optimization

Delivers prescriptive analytics capabilities and decision intelligence to improve decision-making.


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  • 1.  Conflics in the model

    Posted 05/08/15 03:36 AM

    Originally posted by: YahongChen


    Hi,

        I'm trying to use CPLEX CP optimizer to solve the MILP dispatch problem in power system.

        In the model, I have to write the minimum on and off time constraints for the power plant ,after adding that in the model and run it there shows  conflics finds and

    Conflict refining terminated

    ! ----------------------------------------------------------------------------

    ! Conflict status : Terminated normally, conflict found

    please help me rewrite the constraints.

    Here is my constraint:

    Minimum on and off time constraints for the units:


    Ton[i][t]==(Ton[i][t-1]+1)*status[i][t];
    (status[i][t-1]-status[i][t])*(Ton[i][t-1]-Tonmin[i])>0;
    (status[i][t]-status[i][t-1])*(Toff[i][t-1]-Toffmin[i])>0;
    Toff[i][t]==(Toff[i][t-1]+1)*(1-status[i,t]);

    Where Ton calculate the on time, Tonmin is the allowable minimum on time and it's value is given such as 3, Toff calculate the off time,Toffmin is the allowable minimum off time and it's value is given such as 4, status is the on and off status of the power plant and it is 0-1 variable, i represent the i th plant, t represent the t th time unit.

    If the plant is turned on, it has to be on for at least Tonmin consective time units,and when it is switched off ,it will remain off for Toffmin consective time units.
     

     

     

     

     

     

     

     


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    #DecisionOptimization


  • 2.  Re: Conflics in the model

    Posted 05/11/15 03:22 AM

    Originally posted by: PhilippeLaborie


    If a conflict is found, it means that the problem was shown by the engine to be infeasible. You should try to display a minimal conflict (using function writeConflict once the conflict refiner has found a conflict), this will give you a small subset of your constraints that explain the infeasibility of the problem.

    Philippe


    #ConstraintProgramming-General
    #DecisionOptimization