In this tutorial, I show implementation of the ZDT1 multi-objective test problem and optimize it using the built-in Multi-objective Genetic Algorithm in MATLAB. The given objective function is a standard test function that helps a beginner user to understand the basic concept of optimization in MATLAB easier. The given objective function or fitness function has one vector input including ‘n’ variables and two outputs (objective values). I write two separate functions one for the fitness function and one for the main algorithm. I plot the pareto-front that illustrates the obtained solutions in a proper way. We use different setting of the algorithm using the ‘optimoptions’ function.
For a simple tutorial on optimization using Genetic Algorithm with single objective functions without constraints see this post.
For a simple tutorial on optimization using Genetic Algorithm with single objective functions with constraints see this post.
For a tutorial on multi-objective optimization using Genetic Algorithm see this post.
for a tutorial on Mixed-integer optimization problem using linear programming see this post.
for a tutorial on Pattern Search optimization in MATLAB see this post.
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