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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/24472

Title: Particle Swarm Optimization for Global Optimization Problems
Authors: Hsin-Chuan Kuo;Jiang-Ren Chang;Ching-Hsiang Liu
Contributors: NTOU:Department of Systems Engineering and Naval Architecture
Keywords: optimization problems;grouping wisdom;particle swarm optimization
Date: 2006
Issue Date: 2011-10-20T08:12:26Z
Publisher: Journal of Marine Science and Technology
Abstract: Abstract:In this paper, the particle swarm optimization (PSO), originated as a simulation of a simplified social system with swarm intelligence and having exploring and exploiting characteristics of the particle swarm, is adopted to deal with the global optimization problems. To begin with, four non-linear two-dimensional functions are adopted as benchmark examples for determining the suitable ranges of parameters in the PSO. It is found that uses of the PSO can make the search quickly converge to the global optimum. Then, several benchmark functions below ten-dimensions are adopted especially for comparisons of search efficiency on the PSO and other algorithms. Results show that the proposed approach is not only superior to other algorithms but also has the higher success rate. Finally, the PSO is also applied to deal with the optimization problem of a grillage structure. Optimization solutions of the success rate and the used average generation show that the PSO also has the better performance for the optimal design of structures with constraints.
Relation: 14(3), pp.170-181
URI: http://ntour.ntou.edu.tw/handle/987654321/24472
Appears in Collections:[系統工程暨造船學系] 期刊論文

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