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Season-Cycling Algorithm for Global Optimizations
H. C. Kuo;J. L. Wu;W. F. Chen;C. J. Chen
|Contributors: ||NTOU:Department of Systems Engineering and Naval Architecture|
Particle Swarm Optimization;Global Optimization;Season-Cycling
|Issue Date: ||2011-10-20T08:12:37Z
Abstract:An innovative season-cycling algorithm far global optimizations has been developed based on each season's lifestyle in agricultural society, seeding in spring, cultivating in summer, harvesting in autumn, and storing in winter. The population-based algorithm, particle swarm optimization (PSO), is used in the proposed algorithm to generate swarm particles and simultaneously provides particle's evolutional information. The particles data in each evolution have been analyzed statistically to End their evolution tendency and then identify the most promising region with the possible global optimal solution. Four benchmark problems with 30/100 dimensions were tested. The results demonstrated the novel season-cycling algorithm proposed in this study as an optimization algorithm with high efficiency and reliability. The proposed algorithm not only introduced a new thinking on improving the PSO performance but offered the structure of identifying the promising region while population-based algorithms are applied.
|Relation: ||27(1), pp.41-50|
|Appears in Collections:||[系統工程暨造船學系] 期刊論文|
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