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Indexed by:期刊论文

Date of Publication:2011-01-01

Journal:Journal of Software

Included Journals:EI、Scopus

Volume:6

Issue:3

Page Number:490-497

ISSN No.:1796217X

Abstract:Artificial bee colony (ABC) algorithm is one of the most recently proposed swarm intelligence algorithms for global numerical optimization. It performs well in most cases; however, there still exist some problems it cannot solve very well. This paper presents a novel hybrid Hooke Jeeves ABC (HJABC) algorithm with intensification search based on the Hooke Jeeves pattern search and the ABC. The main purpose is to demonstrate how the standard ABC can be improved by incorporating a hybridization strategy. The proposed algorithm is tested on a comprehensive set of 36 complex benchmark functions and a slope stability analysis problem including a wide range of dimensions. Comparisons are made with the basic ABC and some recent algorithms. Numerical results show that the new algorithm is promising in terms of convergence speed, success rate and solution accuracy. ? 2011 Academy Publisher.