A novel multi-objective PSO algorithm for constrained optimization problems

Authors:
Jingxuan Wei;Yuping Wang
Affiliations:
School of Science, Xidian University, Xi'an, China;School of Computer Science and Technology, Xidian University, Xi'an, China
Venue:
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Year:
2006

Citing 3
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Abstract

A new approach is presented to handle constrained optimization by using PSO algorithm. It neither uses any penalty function in the proposed PSO algorithms. The new technique treats constrained optimization as a two-objective optimization, one objective is original objective function, and the other is the degree violation of constraints. As we prefer the second objective, a new crossover operator is designed based on the three-parent crossover operator, which will lead the degree violation of constraints to zero. Then, in order to keep the diversity of the swarm and escape from the local optimum easily, we design a dynamically changing inertia weight. The simulation results indicate the proposed algorithm is effective.