Comprehensive learning particle swarm optimizer for solving multiobjective optimization problems

✍ Scribed by V.L. Huang; P.N. Suganthan; J.J. Liang

• Publisher: John Wiley and Sons
• Year: 2005
• Tongue: English
• Weight: 263 KB
• Volume: 21
• Category: Article
• ISSN: 0884-8173
• DOI: 10.1002/int.20128

✦ Synopsis

This article presents an approach to integrate a Pareto dominance concept into a comprehensive learning particle swarm optimizer ~CLPSO! to handle multiple objective optimization problems. The multiobjective comprehensive learning particle swarm optimizer ~MOCLPSO! also integrates an external archive technique. Simulation results ~obtained using the codes made available on the Web at http://www.ntu.edu.sg/home/EPNSugan! on six test problems show that the proposed MOCLPSO, for most problems, is able to find a much better spread of solutions and faster convergence to the true Pareto-optimal front compared to two other multiobjective optimization evolutionary algorithms.