Binary Hybrid Particle Swarm Optimization with Wavelet Mutation

Tran, Quang-Anh; Dinh, Quan Dang; Jiang, Frank

doi:10.1007/978-3-319-11680-8_21

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2017

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“…Nevertheless, similar to most stochastic algorithms, the performance of PSO algorithm will suffer from a significant degradation when it is applied to multi-dimensional or tightly coupled problems. To improve the performance of the traditional PSO algorithm and overcome the disadvantages of traditional PSO algorithm, different variations are presented and studied, such as hybrid PSO algorithm [7,8], multi-swarm PSO algorithm [9,10] and Quantum-behaved PSO algorithm [11].…”

Section: Introductionmentioning

confidence: 99%

An Orthogonal Multi-Swarm Cooperative PSO Algorithm with a Particle Trajectory Knowledge Base

2017

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Abstract:A novel orthogonal multi-swarm cooperative particle swarm optimization (PSO) algorithm with a particle trajectory knowledge base is presented in this paper. Different from the traditional PSO algorithms and other variants of PSO, the proposed orthogonal multi-swarm cooperative PSO algorithm not only introduces an orthogonal initialization mechanism and a particle trajectory knowledge base for multi-dimensional optimization problems, but also conceives a new adaptive cooperation mechanism to accomplish the information interaction among swarms and particles. Experiments are conducted on a set of benchmark functions, and the results show its better performance compared with traditional PSO algorithm in aspects of convergence, computational efficiency and avoiding premature convergence.

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