A novel hybrid differential evolution and particle swarm optimization algorithm for unconstrained optimization

Authors:
Changsheng Zhang;Jiaxu Ning;Shuai Lu;Dantong Ouyang;Tienan Ding
Affiliations:
Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education, Changchun 130012, China;Institute of Grassland Science, Northeast Normal University, China;Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education, Changchun 130012, China;Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education, Changchun 130012, China;Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education, Changchun 130012, China
Venue:
Operations Research Letters
Year:
2009

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Abstract

An algorithm called DE-PSO is proposed which incorporates concepts from DE and PSO, updating particles not only by DE operators but also by mechanisms of PSO. The proposed algorithm is tested on several benchmark functions. Numerical comparisons with different hybrid meta-heuristics demonstrate its effectiveness and efficiency.