Title: A hybrid PSO with EM for global optimisation

Authors: Ye Tian, Dayou Liu, Xin Ma, Changsheng Zhang

Addresses: College of Computer Science and Technology, Jilin University, 2699 Qianjin Street, Changchun, 130012, China; Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, 2699 Qianjin Street, Changchun, 130012, China. ' College of Computer Science and Technology, Jilin University, 2699 Qianjin Street, Changchun, 130012, China; Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, 2699 Qianjin Street, Changchun, 130012, China. ' College of Computer Science and Technology, Jilin University, 2699 Qianjin Street, Changchun, 130012, China; Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, 2699 Qianjin Street, Changchun, 130012, China. ' College of Computer Science and Technology, Jilin University, 2699 Qianjin Street, Changchun, 130012, China; Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, 2699 Qianjin Street, Changchun, 130012, China

Abstract: Heuristic optimisation provides a robust and efficient approach for solving complex real-world problems. The focus of this research is on a hybrid method combining two heuristic optimisation techniques, particle swarm optimisation (PSO) and electromagnetism-like (EM) mechanism, called PSO-EM, for the global optimisation of functions. This hybrid technique incorporates concepts of PSO and EM and creates individuals in a new generation not only by features of PSO, but also by attraction-repulsion mechanism of EM. A numerical study is carried out using a set of 13 test problems, some of which are inspired by practical applications. Results show that the new algorithm is much more robust and efficient than some existing PSO algorithms.

Keywords: global optimisation; heuristic optimisation; particle swarm optimisation; PSO; electromagnetism; hybrid optimisation; attraction; repulsion.

DOI: 10.1504/IJMIC.2009.030079

International Journal of Modelling, Identification and Control, 2009 Vol.8 No.4, pp.327 - 334

Published online: 09 Dec 2009 *

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