Multiple population Genetic Algorithm

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Hari
Hari 2022-9-14
评论： Walter Roberson 2022-9-15
I am using the built in GA function for optimisation with customised creation, crossover, mutation and fitness functions. I have tried 10 runs of GA separately for the same problem and the optimum results is seen to vary in each case. In few cases I have obtained the Global minimum as solution (I have tried on a problem whose global minimum solution is known to me). In other cases the solution is getting stuck at a local minimia. I would like to try a Multiple Population Genetic Algorithm to prevent it from getting stuck at a local minima. Is there a way to implement this using the built in GA function in MATLAB?

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Walter Roberson
Walter Roberson 2022-9-14
Sorry, No.
The internal code for unconstrained ga is able to handle "sub-populations", which for that routine is activated by the PopulationSize option being a vector of values.
However... the public ga() interface does not permit inputting a vector.
For further discussion on subpopulations, see https://www.mathworks.com/support/search.html/answers/447715-subpopulations-and-parallel-processing-in-ga.html
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Walter Roberson
Walter Roberson 2022-9-15
The internal code that permits vector population size, is inside a "private" directory, and so cannot be called by functions outside the parent directory.

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Sam Chak
Sam Chak 2022-9-14
Hi @Hari
You can try specifying the Population Options in optimoptions().
https://www.mathworks.com/help/gads/options-in-genetic-algorithm.html#gaoptionsdemo-4
https://www.mathworks.com/help/gads/genetic-algorithm-options.html#f14223
opts = optimoptions(@ga, 'PlotFcn', {@gaplotbestf, @gaplotstopping});
opts.PopulationSize = ... ;
opts.InitialPopulationRange = ... ;

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