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how to use genetic algorithm (GA) in matlab ?

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Hi, all
% input_data shape = [ M x N x T ] ( channel, trials, time sample )
% ga : Find minimum of function using genetic algorithm
ga(fitness_function_my_own, input_data)
I want to find a few channels that minimize the fitness function for M channels, and the question is two.
Q1. I wonder if ga can be applied to the matrix data ?
Q2. I know that parameters that need to be set, such as crossover probability and mutation probability, are theoretically necessary to apply ga.
Is it necessary to modify the ga function directly in the file implemented to apply this option to the corresponding function?

Accepted Answer

Walter Roberson
Walter Roberson on 15 Feb 2021
Q1. I wonder if ga can be applied to the matrix data ?
Yes, but fitness_function_my_own must return a scalar.
If you want fitness_function_my_own to return multiple values because you are trying to optimize multiple functions at the same time, then you need gamultiobj() instead of ga()
Is it necessary to modify the ga function directly in the file implemented to apply this option to the corresponding function?
No, see gaoptimset() to construct an options structure. The options structure must be passed as either the 10th or 11th parameter to ga(); you can use [] for parameters you are not using. For example,
ga(fitness_function_my_own, 3, [], [], [], [], [], [], [], options)
Note: you do not pass your data directly in to fitness_function_my_own . Instead see http://www.mathworks.com/help/matlab/math/parameterizing-functions.html
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