期刊
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
卷 40, 期 6, 页码 1634-1648出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMCB.2010.2043527
关键词
Composite particle; dynamic optimization problem (DOP); particle swarm optimization (PSO); scattering operator; velocity-anisotropic reflection (VAR)
类别
资金
- National Natural Science Foundation (NNSF) of China [70931001, 70771021, 60821063, 70721001]
- Ph.D. Programs Foundation of the Ministry of Education of China [200801450008]
- Engineering and Physical Sciences Research Council of U.K. [EP/E060722/1]
- EPSRC [EP/E060722/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/E060722/1] Funding Source: researchfish
In recent years, there has been a growing interest in the study of particle swarm optimization (PSO) in dynamic environments. This paper presents a new PSO model, called PSO with composite particles (PSO-CP), to address dynamic optimization problems. PSO-CP partitions the swarm into a set of composite particles based on their similarity using a worst first principle. Inspired by the composite particle phenomenon in physics, the elementary members in each composite particle interact via a velocity-anisotropic reflection scheme to integrate valuable information for effectively and rapidly finding the promising optima in the search space. Each composite particle maintains the diversity by a scattering operator. In addition, an integral movement strategy is introduced to promote the swarm diversity. Experiments on a typical dynamic test benchmark problem provide a guideline for setting the involved parameters and show that PSO-CP is efficient in comparison with several state-of-the-art PSO algorithms for dynamic optimization problems.
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