Title: Particle based on biogeography-based optimisation for global optimisation problems

Authors: Quanxi Feng; Sanyang Liu; Guoqiang Tang; Huazhou Chen

Addresses: School of Science, Xidian University, Xi'an 710071, China; School of Science, Guilin University of Technology, Guilin 541004, China ' School of Science, Xidian University, Xi'an 710071, China ' School of Science, Guilin University of Technology, Guilin 541004, China ' School of Science, Guilin University of Technology, Guilin 541004, China

Abstract: Biogeography-based optimisation is an emerging evolutionary optimisation algorithm based on biogeography theory. This paper proposes a hybrid algorithm through hybridisation of biogeography-based optimisation and particle swarm optimisation. The hybridisation embeds the position updating equation of PSO into migration operator of BBO to accelerate convergence speed. Cauchy mutation is also integrated to enhance population diversity and implement selection operator to preserve fitter habitats for the subsequent generation. Experimental tests are conducted on 23 benchmark functions. Simulation results and comparisons show that the new algorithm is an efficient algorithm. Compared with other state-of-the-art BBO algorithms and evolutionary algorithms, the proposed algorithm performs better or at least comparably in terms of solution's quality and convergent speed. Finally, the influence of the proportional ratio in migration operator on the performance is also investigated.

Keywords: biogeography based optimisation; BBO; hybrid migration operator; evolutionary algorithms; particle swarm optimisation; PSO; simulation; global optimisation.

DOI: 10.1504/IJICA.2013.063028

International Journal of Innovative Computing and Applications, 2013 Vol.5 No.4, pp.228 - 239

Received: 04 Jan 2014
Accepted: 06 Jan 2014
Published online: 31 Jul 2014 *

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