This code is a demo of using Genetic Algorithms (GA) to solve a simple constrained multi-objective optimization (MOO) problem.
The objective is to find the pareto front of the MOO problem defined as follows:
f1(X) = 2*x1 + 3*x2
f2(X) = 2/x1 + 1/x2
10 > x1 > 20
20 > x2 > 30
The set of non-dominated solutions is plotted in the objective space, and displayed in the console.
Sam Elshamy (2020). Constrained MOO using GA (ver. 2) (https://www.mathworks.com/matlabcentral/fileexchange/29806-constrained-moo-using-ga-ver-2), MATLAB Central File Exchange. Retrieved .
any examples of source code on multiobjective optimization with mix integer variables?I have 3 objective functions, 6 decision variables....thanks very much
@Yu-Yun. You are right. I fixed this bug and other bugs I found in my code and uploaded a revised version.
I think line 68 and 69 are supposed to be
Now available in Toolbox format.
Update: Bugs in line 68 and 69 and others are now fixed. Thanks to Yu-Yun