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A New Improved Quantum Evolution Algorithm with Local Search Procedure for Capacitated Vehicle Routing Problem

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  • Ligang Cui
  • Lin Wang
  • Jie Deng
  • Jinlong Zhang

Abstract

The capacitated vehicle routing problem (CVRP) is the most classical vehicle routing problem (VRP); many solution techniques are proposed to find its better answer. In this paper, a new improved quantum evolution algorithm (IQEA) with a mixed local search procedure is proposed for solving CVRPs. First, an IQEA with a double chain quantum chromosome, new quantum rotation schemes, and self-adaptive quantum Not gate is constructed to initialize and generate feasible solutions. Then, to further strengthen IQEA's searching ability, three local search procedures 1-1 exchange, 1-0 exchange, and 2-OPT, are adopted. Experiments on a small case have been conducted to analyze the sensitivity of main parameters and compare the performances of the IQEA with different local search strategies. Together with results from the testing of CVRP benchmarks, the superiorities of the proposed algorithm over the PSO, SR-1, and SR-2 have been demonstrated. At last, a profound analysis of the experimental results is presented and some suggestions on future researches are given.

Suggested Citation

  • Ligang Cui & Lin Wang & Jie Deng & Jinlong Zhang, 2013. "A New Improved Quantum Evolution Algorithm with Local Search Procedure for Capacitated Vehicle Routing Problem," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-17, December.
    • Handle: RePEc:hin:jnlmpe:159495
    DOI: 10.1155/2013/159495
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    Cited by:

    1. Ines Sbai & Saoussen Krichen & Olfa Limam, 2022. "Two meta-heuristics for solving the capacitated vehicle routing problem: the case of the Tunisian Post Office," Operational Research, Springer, vol. 22(1), pages 507-549, March.

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