| ○種別 (必須): | □ | 学術論文 (審査論文)
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| ○言語 (必須): | □ | 日本語
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| ○著者 (必須): | 1. | (英) (日) 上村 健人 (読)
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| 2. | (英) (日) 木下 峻一 (読)
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| 3. | 永田 裕一 ([徳島大学.大学院社会産業理工学研究部.理工学域.知能情報系.情報工学分野]/[徳島大学.理工学部.理工学科.知能情報コース.情報工学講座])
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| 4. | (英) (日) 小林 重信 (読)
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| 5. | 小野 功
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| ○題名 (必須): | □ | (英) Big-valley Explorer: A Framework of Real-coded Genetic Algorithms for Multi-funnel Function Optimization (日) 大域的多峰性関数最適化のための実数値GAの枠組みBig-valley Explorerの提案
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| ○要約 (任意): | □ | (英) This paper proposes a new framework of real-coded genetic algorithms (RCGAs) for the multi-funnel function optimization. The RCGA is one of the most powerful function optimization methods. Most conventional RCGAs work effectively on the single-funnel function that consists of a single big-valley. However, it is reported that they show poor performance or, sometimes, fail to find the optimum on the multi-funnel function that consists of multiple big-valleys. In order to remedy this deterioration, Innately Split Model (ISM) has been proposed as a framework of RCGAs. ISM initializes an RCGA in a small region and repeats a search with the RCGA as changing the position of the region randomly. ISM outperforms conventional RCGAs on the multi-funnel functions. However, ISM has two problems in terms of the search efficiency and the difficulty of setting parameters. Our proposed method, Big-valley Explorer (BE), is a framework of RCGAs like ISM and it has two novel mechanisms to overcome these problems, the big-valley estimation mechanism and the adaptive initialization mechanism. Once the RCGA finishes a search, the big-valley estimation mechanism estimates a big-valley that the RCGA already explored and removes the region from the search space to prevent the RCGA from searching the same big-valley many times. After that, the adaptive initialization mechanism initializes the RCGA in a wide unexplored region adaptively to find unexplored big-valleys. We evaluate BE through some numerical experiments with both single-funnel and multi-funnel benchmark functions. (日)
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| ○キーワード (推奨): | 1. | (英) function optimization (日) (読)
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| 2. | (英) multi-funnel function (日) (読)
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| 3. | (英) real-coded genetic algorithms (日) (読)
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| 4. | (英) ISM (日) (読)
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| ○発行所 (推奨): | □ | (英) The Japanese Society for Evolutionary Computation (日) 進化計算学会 (読)
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| ○誌名 (必須): | □ | 進化計算学会論文誌 (進化計算学会)
(eISSN: 2185-7385)
| ○ISSN (任意): | □ | 2185-7385
ISSN: 2185-7385
(eISSN: 2185-7385) Title: 進化計算学会論文誌Supplier: 進化計算学会 (J-STAGE)
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| ○巻 (必須): | □ | 4
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| ○号 (必須): | □ | 1
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| ○頁 (必須): | □ | 13 27
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| ○年月日 (必須): | □ | 西暦 2013年 3月 初日 (平成 25年 3月 初日)
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| ○URL (任意): | □ | https://ci.nii.ac.jp/naid/130004965145/
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| ○DOI (任意): | □ | 10.11394/tjpnsec.4.1 (→Scopusで検索)
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| ○CRID (任意): | □ | 1390001205366429312
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| ○NAID : | □ | 130004965145
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