Adaptive particle swarm optimization using information about global best

• Teruyoshi Yamaguchi

• Nobuhiro Iwasaki

• Keiichiro Yasuda

Abstract

The Particle Swarm Optimization method is one of the most powerful optimization methods available for solving global optimization problems. However, knowledge of adaptive strategies for tuning the parameters of the method for application to large‐scale nonlinear nonconvex optimization problems is as yet limited. This paper describes an adaptive strategy for tuning the parameters of the PSO method based on some numerical analysis of the behavior of PSO. The proposed adaptive tuning strategy is based on self‐tuning of the parameters of PSO, which utilizes the information about the frequency of an updated global best of a swarm. The feasibility and advantages of the proposed adaptive PSO algorithm are demonstrated through some numerical simulations using three different typical global optimization test problems. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 159(4): 38– 46, 2007; Published online in Wiley InterScience (<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="http://www.interscience.wiley.com">www.interscience.wiley.com ). DOI 10.1002/eej.20487

Journal

• Electrical Engineering in Japan

  Electrical Engineering in Japan 159 (4), 38-46, 2007-04-13

  Wiley

Keywords

• Electrical and Electronic Engineering
• Energy Engineering and Power Technology

Details

• CRID: 1360008373648374912
• NII Article ID: 210000181864
• DOI: 10.1002/eej.20487
• ISSN: 15206416
• ISSN: 04247760
• Web Site: https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Feej.20487
• Web Site: https://onlinelibrary.wiley.com/doi/pdf/10.1002/eej.20487
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