A Basic Study of The Adaptive Particle Swarm Optimization
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- Ide Azuma
- Tokyo Metropolitan University
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- Yasuda Keiichiro
- Tokyo Metropolitan University
Bibliographic Information
- Other Title
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- 適応型Particle Swarm Optimizationに関する基礎的検討
- テキオウガタ Particle Swarm Optimization ニ カンスル キソテキ ケントウ
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Abstract
This paper points out that meta-heuristics should have not only robustness and adaptability to problems with different structure but also adjustability of parameters included in their algorithms. Particle Swarm Optimization (PSO), whose concept began as a simulation of a simplified social milieu, is known as one of the most powerful optimization methods for solving nonconvex continuous optimization problems. Then, in order to improve adjustability, a new parameter is introduced into particle swarm optimization on the basis of the Proximate Optimality Principle (POP). In this paper, we propose adaptive Particle Swarm Optimization and the effectiveness and the feasibility of the proposed approach are demonstrated on simulations using some typical nonconvex optimization problems.
Journal
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- IEEJ Transactions on Electronics, Information and Systems
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IEEJ Transactions on Electronics, Information and Systems 124 (2), 550-557, 2004
The Institute of Electrical Engineers of Japan
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Details 詳細情報について
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- CRID
- 1390001204606410368
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- NII Article ID
- 10011965947
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- NII Book ID
- AN10065950
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- BIBCODE
- 2004ITEIS.124..550I
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- ISSN
- 13488155
- 03854221
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- NDL BIB ID
- 6841810
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed