Authors: Zhihong Zhang
Addresses: School of Computer and Information Technology, Shangqiu Normal University, Shangqiu 476000, China
Abstract: Differential evolution (DE) is an efficient population-based stochastic search algorithm, which has shown good search abilities on many real-world and benchmark optimisation problems. In this paper, we propose a new multi-population-based DE (MDE) algorithm. In MDE, the original population is divided into multiple subpopulations. For each subpopulation, two DE mutation schemes are alternatives to be conducted. Moreover, a Cauchy mutation operator is utilised to enhance the global search. To verify the performance of MDE, 12 well-known benchmark functions are used in the experiments. Simulation results show that MDE performs better than the standard DE and several other DE variants.
Keywords: differential evolution; multi-population DE; Cauchy mutation; global optimisation.
International Journal of Computing Science and Mathematics, 2015 Vol.6 No.1, pp.88 - 96
Received: 04 Aug 2014
Accepted: 01 Sep 2014
Published online: 19 Feb 2015 *