Cooperatively Coevolving Particle Swarms for Large Scale Optimization

7 years 4 months ago
Cooperatively Coevolving Particle Swarms for Large Scale Optimization
—This paper presents a new cooperative coevolving particle swarm optimization (CCPSO) algorithm in an attempt to address the issue of scaling up particle swarm optimization (PSO) algorithms in solving large-scale optimization problems (up to 2000 real-valued variables). The proposed CCPSO2 builds on the success of an early CCPSO that employs an effective variable grouping technique random grouping. CCPSO2 adopts a new PSO position update rule that relies on Cauchy and Gaussian distributions to sample new points in the search space, and a scheme to dynamically determine the coevolving subcomponent sizes of the variables. On high-dimensional problems (ranging from 100 to 2000 variables), the performance of CCPSO2 compared favorably against a state-of-the-art evolutionary algorithm sep-CMA-ES, two existing PSO algorithms, and a cooperative coevolving differential evolution algorithm. In particular, CCPSO2 performed significantly better than sep-CMA-ES and two existing PSO algorithms on...
Xiaodong Li, Xin Yao
Added 29 Sep 2012
Updated 29 Sep 2012
Type Journal
Year 2012
Where TEC
Authors Xiaodong Li, Xin Yao
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