Binary Particle Swarm Optimization: Challenges and new Solutions

Binary Particle Swarm Optimization: Challenges and new Solutions

Abstract

Over the last decades there has been a growing interest in algorithms inspired by the observation of natural phenomenon. Recently-introduced Binary Particle Swarm Optimization (BPSO) is considered as a powerful solution scheme, which is able to help PSO to be applied to continuous and discrete binary optimization problems. In this paper, the BPSO is addressed in details; the disadvantages of the BPSO are investigated and the solutions to these disadvantages are introduced. To show the efficiency and effectiveness of the proposed BPSOs over the original BPSO, they are applied to several benchmark problems including unimodal and multimodal functions. The results obtained show that the proposed BPSOs perform much better than the original BPSO and can be considered as alternative approaches for solving different problems.

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