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 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.
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Keyword(in English) Ant Colony Optimization / Parallel Computing / OpenMP / Scheduling / Rolling Stock Planning
Paper # NLP2013-138
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Conference Information
Committee NLP
Conference Date 2014/1/14(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
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