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A Multi-objective constraint-handling method with PSO algorithm for constrained engineering optimization problems
conference contribution
posted on 2017-12-06, 00:00 authored by Xinghuo YuXinghuo Yu, Dujuan LiDujuan LiThis 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.
Funding
Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)
History
Start Page
1528End Page
1535Number of Pages
8Start Date
2008-01-01ISBN-13
9781424418237Location
Hong Kong, ChinaPublisher
IEEEPlace of Publication
USAPeer Reviewed
- Yes
Open Access
- No
External Author Affiliations
Faculty of Business and Informatics; RMIT University; TBA Research Institute;Era Eligible
- Yes