Efficient Local Search Limitation Strategies in Memetic Algorithm

DOI Web Site 12 References Open Access
  • Nagata Yuichi
    Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology
  • Kobayashi Shigenobu
    Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology
  • Tojo Satoshi
    School of Information Science, Japan Advanced Institute of Science and Technology

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  • 効果的な局所探索制限によるMemetic Algorithmの高速化

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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.

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