NSGA-II是一个很成熟的多目标优化算法了。根本原理还是Patero最优问题。
NSGA-II matlab代码，网上比较有名的是Aravind Seshadri写的，采用的是BSD许可证。
这里做一下简要的使用介绍：
objective_description_function.m 要自己重写，主要是定义优化目标函数个数、随机种子取值范围等等。
evaluate_objective.m 是优化目标函数，当然要自己重写了。
nsga_2.m是启动函数，要设置两个参数。
其他m文件基本不用改动。具体介绍看程序包里的html说明，算法看pdf文件。
下面拷贝一下作者的对该工具箱的介绍。作者也说了，不在维护该程序了，有错误只能自己改了。
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.
For more information on NSGA-II visit Kanpur Genetic Algorithm Laboratory at http://www.iitk.ac.in/kangal/
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.
Update (January 27, 2009): I am unable to support user's request to modify this program to incorporate constraints in the optimization program since I have no time to delve into this field. Hence effective today (January 27, 2009) I release this program under GPLv3. This means that anyone and everyone can modify this code as and how they wish. Enjoy! But do remember to contribute the code back to the community.
Effective July 17, 2009 this code is re-licensed under BSD license to comply with Mathworks policy on submissions to MATLAB central.
Note: I no longer have the resources to maintain this code.
