Binary solutions with GA

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Loic Wilfried Biakeu Njia
Loic Wilfried Biakeu Njia 2017 年 6 月 20 日
コメント済み: Brendan Hamm 2017 年 9 月 30 日
I am currently working with GA on resource allocation and the goal is to find binary solutions with a non linear objective and linear constraints.
At the beginning of the project, I had a problem with more than 700 variables with many constraints and the solutions that I had from GA were very irrelevant. I thought the size of the problem was the issue.
So I broke down the problem into many models in order to have less that hundreds variables (in occurrence 30 variables for the current model I am building) and around hundreds constraints too for each model (in occurrence 95 linear constraints for the same current model). Besides, some of the constraints are normally equality constraints that I transformed into inequality constraints to help GA to find a solution. BUT at the end I still have solutions that don't correspond to the constraints. For the instance, for example if we want to allocate 30 bags in 5 cabinets so that each bag is allocated only in one cabinet, I got some results where one bag is allocated in many cabinets, even though the inequality constraints that I wrote seem totally correct.
I have this report at the end "Optimization terminated: average change in the penalty fitness value less than options.FunctionTolerance and constraint violation is less than options.ConstraintTolerance".
I don't really know what to do with this problem and I am quite in a need of a solution for an industrial (confidential) problem after having purchased GA weeks ago (the trials for smaller sizes seemed to work previously). Please could you give any support for that?
  8 件のコメント
Walter Roberson
Walter Roberson 2017 年 6 月 28 日
Ah, good point about the number sometimes having to vary.


回答 (1 件)

Brendan Hamm
Brendan Hamm 2017 年 9 月 20 日
This will be a bit length to answer this question again, but I have provided a way you can solve this problem in a previous post:
This does use a multiobjective problem, but the idea of writing the population, crossover and mutation functions is the same.
  2 件のコメント
Brendan Hamm
Brendan Hamm 2017 年 9 月 30 日
If you post it on here I will take a look when I have some time and suggest some possible alternatives.


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