Mixed Integer Linear Programming using GA for solution generation of network topology

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Hello,
I'm trying to use mixed integer linear programming (MILP) as recommended by Alan Weiss to solve an optimization network topology problem.
I've set all of the parameters, as documentation about MILP states (adapted to my problem), but when I run the GA function some generated solutions do not respect what I initially had defined.
I have 41 binary variables corresponding to all branches of a network composed by 30 bus with 6 generators. For this network to be radial, I need in all generated solutions to be valid ones, having exactly 24 (30-6) active branches, corresopnding to 24 1's in the solution vector x.
The problem is that I am having many solutions being evaluated by ff that do not verify this restriction.
I don't know if my text is clear, but if you can help me I really appreciate.
Best regards, Vitor Ribeiro.

Accepted Answer

Matt J
Matt J on 26 Aug 2014
Edited: Matt J on 26 Aug 2014
If it's a MILP, it might be more robust, as well as easier, to use intlinprog, as opposed to ga. Beyond that, we cannot say what's wrong without seeing your code.
  5 Comments
Vitor Ribeiro
Vitor Ribeiro on 10 Sep 2014
In fact, after some simulations, with GA working in same parameters as I initially state, I can see that when it finds a feasible solution GA rapidly learn and apparently converge because it is evaluating more feasible solutions around the 1st one it reach.
In many literature there are results showing that GA is a really good choice for solving problems of topology optimization with his basic heuristic formulation. I'm not certain about the mean code of GA function but I am convinced that it respects the heuristic core.
I'm not saying that GA in matlab works better then any other optimization function cause I do not have the knowledge for that. I don't know if BINTPROG or even INTLINPROG works better. I am interested in see documentation explaining how it works before seeing how it's used. If you can provide some link it would be really helpful.
After I can see how it works this functions, about how the solutions are generated or even search space composed by solutions are really searched by this algorithms, if they have an heuristic base, I would be able to choose research more in literature and probably understand which works better before I apply it in my problem indiscriminately.
Thank you all for your answers. I really appreciate each one in discussion. Hope you can help me. Regards, Vitor Ribeiro.
Matt J
Matt J on 10 Sep 2014
Edited: Matt J on 10 Sep 2014
I can see that when it finds a feasible solution GA rapidly learn and apparently converge because it is evaluating more feasible solutions around the 1st one it reach.
You need to verify, though, that it converges to the right thing. I.e., check that the final solution and objective value it gives agree with intlinprog. You also need to check that it does so 99% of the time, and not say 80%.
I do not have the knowledge for that. I don't know if BINTPROG or even INTLINPROG works better. I am interested in see documentation explaining how it works before seeing how it's used. If you can provide some link it would be really helpful.
Google's your friend,

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