階層型アントコロニー最適化法のマルチコア型並列計算機への実装と性能評価: 定期検査制約を有する車両運用計画問題への適用 (非線形問題)

幸弥 北川; 康孝 辻; 真弘 黒田

階層型アントコロニー最適化法のマルチコア型並列計算機への実装と性能評価: 定期検査制約を有する車両運用計画問題への適用 (非線形問題)

北川幸弥, 辻康孝, 黒田真弘

制御システム

研究成果: ジャーナルへの寄稿 › 学術誌

抄録

We developed Hierarchical Ant Colony Optimization (H-ACO) for solving railway rolling stock planning. H-ACO uses several colonies and allocates them hierarchically. However, it requires a huge amount of computation time for calculation using large number of colonies. In this paper, we implement H-ACO in parallel computation environment with multi-core processor in order to reduce its computation time. The effectiveness of the proposed method is demonstrated through a numerical experiment.

寄稿の翻訳タイトル	Implementation of Hierarchical Ant Colony Optimization on Multi-core Parallel Computer and Its Performance Evaluation
本文言語	日本語
ページ（範囲）	51-55
ページ数	5
ジャーナル	IEICE technical report
巻	113
号	383
出版ステータス	出版済み - 1月 21 2014

文献へのアクセス

http://id.ndl.go.jp/bib/025277841

フィンガープリント

「階層型アントコロニー最適化法のマルチコア型並列計算機への実装と性能評価: 定期検査制約を有する車両運用計画問題への適用 (非線形問題)」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル

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abstract = "We developed Hierarchical Ant Colony Optimization (H-ACO) for solving railway rolling stock planning. H-ACO uses several colonies and allocates them hierarchically. However, it requires a huge amount of computation time for calculation using large number of colonies. In this paper, we implement H-ACO in parallel computation environment with multi-core processor in order to reduce its computation time. The effectiveness of the proposed method is demonstrated through a numerical experiment.",

author = "幸弥北川 and 康孝辻 and 真弘黒田",

year = "2014",

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language = "日本語",

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T2 - 定期検査制約を有する車両運用計画問題への適用 (非線形問題)

AU - 北川, 幸弥

AU - 辻, 康孝

AU - 黒田, 真弘

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AB - We developed Hierarchical Ant Colony Optimization (H-ACO) for solving railway rolling stock planning. H-ACO uses several colonies and allocates them hierarchically. However, it requires a huge amount of computation time for calculation using large number of colonies. In this paper, we implement H-ACO in parallel computation environment with multi-core processor in order to reduce its computation time. The effectiveness of the proposed method is demonstrated through a numerical experiment.

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