Particle Swarm Optimization Algorithm Based on Escape Boundary

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The particle swarm optimization (PSO) is a population-based stochastic evolutionary algorithm, noted for its capability of searching for the global optimum of complex problems. Particles flying out of the solution space will lead to invalid solutions. So often in engineering applications, boundary condition is used to confine the particles within the solution space. In this paper, a new boundary is proposed, which is called as escape boundary. The solution space is divided into three sections, that is, the inside,escape boundary and the outside of the boundary. The location of the global solution in the solution space, accordingly has two types, that is, the global optimum around the center of the solution space, and the global optimum close to the escape boundary. The proposed boundary is introduced into the PSO algorithm, and is compared to the damping boundary. The experimental results show that the PSO based on escape boundary has better search ability and faster convergence rate.

Info:

Periodical:

Advanced Materials Research (Volumes 361-363)

Edited by:

Qunjie Xu, Honghua Ge and Junxi Zhang

Pages:

1426-1431

DOI:

10.4028/www.scientific.net/AMR.361-363.1426

Citation:

W. H. Han "Particle Swarm Optimization Algorithm Based on Escape Boundary", Advanced Materials Research, Vols. 361-363, pp. 1426-1431, 2012

Online since:

October 2011

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$35.00

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