Presentation | 2014-01-21 Implementation of Hierarchical Ant Colony Optimization on Multi-core Parallel Computer and Its Performance Evaluation : Application to Rolling Stock Planning with Regular Inspection Yukiya KITAGAWA, Yasutaka TSUJI, Masahiro KURODA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | 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. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Ant Colony Optimization / Parallel Computing / OpenMP / Scheduling / Rolling Stock Planning |
Paper # | NLP2013-138 |
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Committee | NLP |
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Conference Date | 2014/1/14(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Nonlinear Problems (NLP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Implementation of Hierarchical Ant Colony Optimization on Multi-core Parallel Computer and Its Performance Evaluation : Application to Rolling Stock Planning with Regular Inspection |
Sub Title (in English) | |
Keyword(1) | Ant Colony Optimization |
Keyword(2) | Parallel Computing |
Keyword(3) | OpenMP |
Keyword(4) | Scheduling |
Keyword(5) | Rolling Stock Planning |
1st Author's Name | Yukiya KITAGAWA |
1st Author's Affiliation | Graduate School of Engineering, Kyushu University() |
2nd Author's Name | Yasutaka TSUJI |
2nd Author's Affiliation | Faculty of Engineering, Kyushu University |
3rd Author's Name | Masahiro KURODA |
3rd Author's Affiliation | Kubota Corporation |
Date | 2014-01-21 |
Paper # | NLP2013-138 |
Volume (vol) | vol.113 |
Number (no) | 383 |
Page | pp.pp.- |
#Pages | 5 |
Date of Issue |