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A Multi-objective constraint-handling method with PSO algorithm for constrained engineering optimization problems

conference contribution
posted on 06.12.2017, 00:00 by Xinghuo Yu, Dujuan Li
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.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Start Page

1528

End Page

1535

Number of Pages

8

Start Date

01/01/2008

ISBN-13

9781424418237

Location

Hong Kong, China

Publisher

IEEE

Place of Publication

USA

Peer Reviewed

Yes

Open Access

No

External Author Affiliations

Faculty of Business and Informatics; RMIT University; TBA Research Institute;

Era Eligible

Yes

Name of Conference

Congress on Evolutionary Computation