| ○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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| ○招待 (推奨): |
| ○審査 (推奨): | □ | Peer Review
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| ○カテゴリ (推奨): | □ | 研究
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| ○共著種別 (推奨): | □ | 単独著作 (徳島大学内の単一の研究グループ(研究室等)内の研究 (単著も含む))
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| ○学究種別 (推奨): |
| ○組織 (推奨): |
| ○著者 (必須): | 1. | (英) Terao Keiichiro (日) 寺尾 圭一郎 (読) てらお けいいちろう
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| ○学籍番号 (推奨): | □ | ****
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| 2. | 小野 典彦
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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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| ○題名 (必須): | □ | (英) Parallelization of GA-EAX using Identical Population in all Processes (日) 全プロセスによる同一集団を維持したGA-EAXの並列化
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| ○要約 (任意): | □ | (英) One of the most powerful approximation solution methods for the traveling salesman problem (TSP) is a genetic algorithm using edge assembly crossover (GA-EAX), which has found best-known tours to several 100 thousand points scale TSP instances. However, due to the nature of multi-point search, in many cases GAs take more computation time than local search-based algorithms, and it is difficult to fully exercise the capability of GA-EAX for very large TSP instances having more than 1 million points within a reasonable computation time. In this research, we introduce a MPI parallel implementation of GA-EAX. However, in a naive master slave method, the communication costs between the processes are too high to obtain the effect of parallelization sufficiently. So, we introduce a method to reduce the amount of communication between processes to avoid this problem. We also introduce a MPI/thread hybrid parallel implementation of GA-EAX where each MPI process is executed using multiple threads. Experimental results show that the hybrid parallel model achieved up to 29.4 times speedup using 16 PCs, each with 4 cores. (日)
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| ○キーワード (推奨): | 1. | (英) traveling salesman problem (日) (読)
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| 2. | (英) genetic algorithm (日) (読)
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| 3. | (英) EAX (日) (読)
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| 4. | (英) parallel computing (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): | □ | 8
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| ○号 (必須): | □ | 3
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| ○頁 (必須): | □ | 100 110
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| ○年月日 (必須): | □ | 西暦 2018年 4月 初日 (平成 30年 4月 初日)
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| ○URL (任意): | □ | https://ci.nii.ac.jp/naid/130006668421/
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| ○DOI (任意): | □ | 10.11394/tjpnsec.8.100 (→Scopusで検索)
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| ○PMID (任意): |
| ○CRID (任意): | □ | 1390001205364382848
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| ○NAID : | □ | 130006668421
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| ○指導教員 (推奨): | 1. | 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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