Multi-swarm particle swarm optimiser with Cauchy mutation for dynamic optimisation problems. (25th February 2010)

• Record Type: Journal Article
• Authors: Hu, Chengyu; Wang, Bo; Wang, Yongji
• Is Part Of: International journal of innovative computing and applications. Volume 2:Number 2(2009)
• Page Start: 123
• Page End: 132
• Publication Date: 2010-02-25
• Subjects: multiple swarms -- Cauchy mutation -- dynamic optimisation -- particle swarm optimisation -- multi-swarm PSO; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

Many real-world problems are dynamic, requiring an optimisation algorithm which is able to continuously track a changing optimum over time. In this paper, we present a new variant of particle swarm optimisation (PSO) specifically designed to work well in dynamic environments. The main idea is to divide the population of particles into a set of interacting swarms. These swarms interact locally by dynamic regrouping and dispersing. Cauchy mutation is applied to the global best particle when the swarm detects the environment of the change. The dynamic function [proposed by Morrison and De Jong (1999)] is used to test the performance of the proposed algorithm. The numerical experimental results are compared with other variant PSO from the literature, showing that the proposed algorithm is an excellent alternative to track dynamically changing optima.