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EVOW
2008
Springer

Compound Particle Swarm Optimization in Dynamic Environments

8 years 10 months ago
Compound Particle Swarm Optimization in Dynamic Environments
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.
Lili Liu, Dingwei Wang, Shengxiang Yang
Added 19 Oct 2010
Updated 19 Oct 2010
Type Conference
Year 2008
Where EVOW
Authors Lili Liu, Dingwei Wang, Shengxiang Yang
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