全プロセスによる同一集団を維持したGA-EAXの並列化
書誌事項
- タイトル別名
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- Parallelization of GA-EAX using Identical Population in all Processes
説明
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.
収録刊行物
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- 進化計算学会論文誌
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進化計算学会論文誌 8 (3), 100-110, 2018
進化計算学会
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詳細情報 詳細情報について
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- CRID
- 1390001205364382848
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- NII論文ID
- 130006668421
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- ISSN
- 21857385
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- CiNii Articles
- KAKEN
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- 抄録ライセンスフラグ
- 使用不可