NSGA-II is a very famous multi-objective optimization algorithm. I submitted an example previously and wanted to make this submission useful to others by creating it as a function. Even though this function is very specific to benchmark problems, with a little bit more modification this can be adopted for any multi-objective optimization.

The function is nsga_2(pop,gen). The input arguments for the function are population size and number of generations. For customization purposes the user is free to modify the objective function (function of several decision variables) by modifying an m file (evaluate_objective.m). Couple of sample objective functions is already described in the file. The user also has the freedom to define the decision space.

One of the main applications of multi-objective optimization that I am currently working on is tuning PID controllers using MOEA. I am hoping to share that work with everyone soon.

Feel free to modify the code and I would really appreciate your criticisms/suggestions/comments/bug report/improvements. I am also interested to share my work with someone who is interested to know more about evolutionary algorithms.

Requirements:

· MATLAB Release: R14SP3