MATLAB: Specifying constraints for optimization using GA

constraintscustom functionga

For a customized GA optimization as in the Traveling Salesman Problem example in matlab documentation, how to specify the constraints of optimization? Should it be specified explicitly or should it be included in the crossover and mutation functions?

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As documented, when using a custom population type, "ga ignores all constraints, including bounds, linear constraints, and nonlinear constraints." So your custom creation, crossover, and mutation functions must enforce your constraints.

Alan Weiss

MATLAB mathematical toolbox documentation

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MATLAB: Ga

Interesting idea. This should be possible, probably with non-linear constraint option.

However, (disclaimer: this is just a thought/curiosity, no guarantees at all), what if you just sort x at the beginning of my_fun()? This would enforce the constraint in your fitness function and possibly cause convergence of the guesses. Let me know if/how it works for you.

function z=my_fun(x)
x = sort(x);
a=2;
b=3;
c=1;
z=a*x(1)-b*x(2)+c*x(3);

MATLAB: GA optimization inequality constraints

The construction of the A and b matrices should be,

A=-diff(speye(2000));
b=-0.01*ones(2000,1);

If you have done this, then there is nothing incorrect about the way you have built the constraints, assuming X(i+1)-X(i)>=0.01 are indeed the conditions you want. You should investigate whether the problem truly does have a feasible solution under these constraints and whatever other constraints you have imposed.

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MATLAB: Ga

MATLAB: GA optimization inequality constraints

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