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Title: Compound particle swarm optimization in dynamic environments
Authors: Liu, L
Wang, D
Yang, S
Keywords: Dynamic optimization problems
Compound particle swarm optimization
Evolutionary algorithms
Compound particles
Publication Date: 2008
Publisher: Springer
Citation: EvoWorkshops 2008: Applications of Evolutionary Computing, Lecture Notes in Computer Science 4974: 616 - 625, 2008
Abstract: Adaptation to dynamic optimization problems is currently receiving a growing interest as one of the most important applications of evolutionary algorithms. In this paper, a compound particle swarm optimization (CPSO) is proposed as a new variant of particle swarm optimization to enhance its performance in dynamic environments. Within CPSO, compound particles are constructed as a novel type of particles in the search space and their motions are integrated into the swarm. A special reflection scheme is introduced in order to explore the search space more comprehensively. Furthermore, some information preserving and anti-convergence strategies are also developed to improve the performance of CPSO in a new environment. An experimental study shows the efficiency of CPSO in dynamic environments.
Description: Copyright @ Springer-Verlag Berlin Heidelberg 2008.
Sponsorship: This work was supported by the Key Program of the National Natural Science Foundation (NNSF) of China under Grant No. 70431003 and Grant No. 70671020, the Science Fund for Creative Research Group of NNSF of China under Grant No. 60521003, the National Science and Technology Support Plan of China under Grant No. 2006BAH02A09 and the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant No. EP/E060722/1.
ISSN: 0302-9743
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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