Title: Particle swarm optimisation based on self-organising topology driven by fitness with different links removing strategies

Authors: Simin Mo; Jianchao Zeng

Addresses: College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, Gansu 730050, China; Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, No. 66 Waliu Road, Wanbailin District, Taiyuan, Shanxi, 030024, China. ' Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, No. 66 Waliu Road, Wanbailin District, Taiyuan, Shanxi, 030024, China

Abstract: In this paper, a novel particle swarm optimisation (PSO) based on self-organising topology driven by fitness (PSO-SOTDF) is proposed. The topology will be gradually generated as the construction process and the optimisation process progress synchronously. And the construction process of topology involves operations of adding and removing links under invariable network sizes. Further, due to the operation of removing links influencing topology characteristics heavily, three kinds of links removing strategies are designed, which are referred to as Removal Strategy I, II and III. To obtain deep insights, the PSO-SOTDF with Removal Strategy I, II and III are used to solve benchmarks. Simulation results show that Removal Strategy I is more effective than other links removing strategies. In addition, the performance of PSO-SOTDF with Removal Strategy I is compared with other variants of PSO. Simulation results indicate that PSO-SOTDF with Removal Strategy I is competitive.

Keywords: particle swarm optimisation; PSO; self-organising topology driven by fitness; SOTDF; link removing strategies; simulation.

DOI: 10.1504/IJICA.2012.046774

International Journal of Innovative Computing and Applications, 2012 Vol.4 No.2, pp.119 - 132

Available online: 07 May 2012 *

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