Computational Property of Hybrid Methods with PSO and DE
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- Muranaka Kenichi
- Graduate School of Science and Technology, Keio University
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- Aiyoshi Eitaro
- Graduate School of Science and Technology, Keio University
Bibliographic Information
- Other Title
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- PSOとDEによるハイブリッド手法の計算特性
- PSO ト DE ニ ヨル ハイブリッド シュホウ ノ ケイサン トクセイ
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Abstract
In this paper, we present a new type of hybrid methods for global optimization with Particle Swarm Optimization (PSO) and Differential Evolution (DE), which have attracted interests as heuristic and global optimization methods recently. Concretely, “p-best solutions” as the targets of PSO's particles are actuated by DE's evolutional mechanism in order to promote PSO's global searching ability. The presented hybrid method works effectively because PSO acts as a local optimizer and DE plays a role as a global optimizer. To evaluate performance of the hybridization, our method is applied to some benchmarks and is compared with the separated PSO and DE. Through computer simulations, it is certified that the proposed hybrid method performs fairy better than their separated algorithm.
Journal
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- IEEJ Transactions on Electronics, Information and Systems
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IEEJ Transactions on Electronics, Information and Systems 132 (7), 1128-1135, 2012
The Institute of Electrical Engineers of Japan
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Keywords
Details 詳細情報について
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- CRID
- 1390001204607329920
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- NII Article ID
- 10030778374
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- NII Book ID
- AN10065950
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- BIBCODE
- 2012ITEIS.132.1128M
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- ISSN
- 13488155
- 03854221
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- NDL BIB ID
- 023887735
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed