A Simple but Efficient Ranking-Based Differential Evolution
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- LI Jiayi
- Faculty of Engineering, University of Toyama
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- YANG Lin
- Faculty of Engineering, University of Toyama
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- YI Junyan
- Beijing University of Civil Engineering and Architecture
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- YANG Haichuan
- Faculty of Engineering, University of Toyama
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- TODO Yuki
- Faculty of Electrical, Information and Communication Engineering, Kanazawa University
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- GAO Shangce
- Faculty of Engineering, University of Toyama
Description
<p>Differential Evolution (DE) algorithm is simple and effective. Since DE has been proposed, it has been widely used to solve various complex optimization problems. To further exploit the advantages of DE, we propose a new variant of DE, termed as ranking-based differential evolution (RDE), by performing ranking on the population. Progressively better individuals in the population are used for mutation operation, thus improving the algorithm's exploitation and exploration capability. Experimental results on a number of benchmark optimization functions show that RDE significantly outperforms the original DE and performs competitively in comparison with other two state-of-the-art DE variants.</p>
Journal
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- IEICE Transactions on Information and Systems
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IEICE Transactions on Information and Systems E105.D (1), 189-192, 2022-01-01
The Institute of Electronics, Information and Communication Engineers
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Keywords
Details 詳細情報について
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- CRID
- 1390290617367836800
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- NII Article ID
- 130008138797
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- ISSN
- 17451361
- 09168532
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- Text Lang
- en
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
- KAKEN
- OpenAIRE
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- Abstract License Flag
- Disallowed