Authors: Lijin Wang; Yiwen Zhong; Yilong Yin
Addresses: School of Computer Science and Technology, Shandong University, Jinan, China; College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China ' College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China ' School of Computer Science and Technology, Shandong University, Jinan, China
Abstract: This paper proposes an improved hybrid cooperative algorithm that combines cooperative cuckoo search algorithm and particle swarm optimisation, called HCCSPSO. The cooperative co-evolutionary framework is applied to cuckoo search algorithm to implement dimensional cooperation. The particle swarm optimisation algorithm, viewed as a cooperative component, is embedded in the back of the cuckoo search algorithm. During iteration, the best solution obtained by the previous cooperative component is randomly embedded in the last one to avoid the pseudo-minima produced by the previous one, while the subcomponents of best solution from the last cooperative component are also randomly planted in the subcomponents of the previous one. The results of experimental simulations demonstrate the improvement in the efficiency and the effect of the cooperation strategy, and the promising of HCCSPSO.
Keywords: hybrid cuckoo search; cooperative cuckoo search; particle swarm optimisation; PSO; dimensional cooperation; component cooperation; simulation.
International Journal of Computing Science and Mathematics, 2015 Vol.6 No.1, pp.18 - 29
Received: 18 Jul 2014
Accepted: 22 Aug 2014
Published online: 19 Feb 2015 *