Multi-Objective Optimization 1.0

Operating systemsOS : Windows / Linux / Mac OS / BSD / Solaris
Program licensingScript Licensing : BSD - BSD License
CreatedCreated : Aug 31, 2007
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Conventional optimization algorithms using linear and ...

Conventional optimization algorithms using linear and non-linear programming sometimes have difficulty in finding the global optima or in case of Multi-Objective Optimization by Aravind Seshadri, the pareto front. A lot of research has now been directed towards evolutionary algorithms (genetic algorithm, particle swarm optmization etc) to solve multi objective optimization problems.
Here in this example a famous evolutionary_algorithm, NSGA-II is used to solve two multi-objective optmization problems. Both problems have a continuous decision variable space while the objective space may or may not be continuous. The first example, MOP1, has two objective functions and six decision variables, while the second example, MOP2, has three objective functions and twelve decision variables.
nsga_2. m is the main function (infact it is mainly a script). Kindly read the accompinied pdf file and also published M-files.
Since there has been a lot of interest in evolutionary algorithms, I am sharing my homework files from last semester. Feel free to edit them according to your needs and feel free to post your comments/suggestion/critisim. I am more than happy to hear from your.
Demands:
• MATLAB Release: R14SP1

Multi-Objective Optimization 1.0 scripting tags: problems, multi-objective optimization, decision, algorithms, evolutionary, matlab miscellaneous, evolutionary algorithm. What is new in Multi-Objective Optimization 1.0 software script? - Unable to find Multi-Objective Optimization 1.0 news. What is improvements are expecting? Newly-made Multi-Objective Optimization 1.1 will be downloaded from here. You may download directly. Please write the reviews of the Multi-Objective Optimization. License limitations are unspecified.