A Multi-Objective Constraint-Handling Method with PSO Algorithm for Constrained Engineering Optimization Problems

被引：19
|
作者：
Li, Lily D. [1 ]
Li, Xiaoding [2 ]
Yu, Xinghuo [3 ]
机构：
[1] Univ Cent Queensland, Sch Comp Sci, Rockhampton, Qld, Australia
[2] RMIT Univ, Sch Comp Sci & Informat Technol, Melbourne, Vic, Australia
[3] RMIT Univ, Sch Elect & Comp Engn, Melbourne, Vic, Australia
来源：
2008 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-8 | 2008年
关键词：
D O I：
10.1109/CEC.2008.4630995
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a multi-objective constraint handling method incorporating the Particle Swarm Optimization (PSO) algorithm. The proposed approach adopts a concept of Pareto domination from multi-objective optimization, and uses a few selection rules to determine particles' behaviors to guide the search direction. A goal-oriented programming concept is adopted to improve efficiency. Diversity is maintained by perturbing particles with a small probability. The simulation results on the three engineering benchmark problems demonstrate the proposed approach is highly competitive.
引用
收藏
页码：1528 / +
页数：3
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