人工知能学会論文誌
Online ISSN : 1346-8030
Print ISSN : 1346-0714
ISSN-L : 1346-0714
原著論文
効果的な局所探索制限によるMemetic Algorithmの高速化
永田 裕一小林 重信東条 敏
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ジャーナル フリー

2010 年 25 巻 2 号 p. 299-310

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抄録
Applications of memetic algorithms (MAs) are usually computationally expensive. In this paper we suggest efficient search limiting strategies for local search used in MAs because local search is the most time consuming part of MAs. The suggested strategies are applied to a recently proposed powerful MA for the capacitated vehicle routing problem (CVRP). Experimental results on the well-known benchmarks show a significant speed-up of 80% in running time without worsening the solution quality. Moreover, the MA dominates state-of-the-art heuristics for the CVRP with respect to both the computation time and the solution quality.
著者関連情報
© 2010 JSAI (The Japanese Society for Artificial Intelligence)
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