How to solve an optimization problem in Gurobi Python where decision variables are established within defined functions?
Hello everyone,
I'm trying to implement a optimization problem in Python but using Gurobi module. In a first stage I found the solution for my optimization problem but using a Python own function named scipy.optimize 'Minimize'. However, I have desired to resolve the same problem but with gurobi module from python.
The specific problem is I have some defined functions that are neccesary to calculate some parameters to the cost function.
My function cost has the way as is presented below:
Ppv, PchDh, SoC, Pred, Pout, ens = calcularPotencias(Pinst, Ebat, Pbat) #This line is required to call calcularPotencias function
Exit = np.sum(Cred * Pred)*deltaT + Cpv * Pinst + Ckwh * Ebat + Ckw * Pbat + np.sum(Cens * ens)*deltaT - np.sum(Cout * Pout)*deltaT #This line represents cost function
Pinst, Ebat, Pbat are decision variables. Cred, Cpv, Ckw, Cens and Cout are coefficients. Pred and Pout are parameters that depend on Ppv, PchDh, SoC.
I would like you for any tip that allow me resolve the problem using Gurobi module
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