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An improved ant colony optimization for vehicle routing problem

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  • Yu, Bin
  • Yang, Zhong-Zhen
  • Yao, Baozhen

Abstract

The vehicle routing problem (VRP), a well-known combinatorial optimization problem, holds a central place in logistics management. This paper proposes an improved ant colony optimization (IACO), which possesses a new strategy to update the increased pheromone, called ant-weight strategy, and a mutation operation, to solve VRP. The computational results for fourteen benchmark problems are reported and compared to those of other metaheuristic approaches.

Suggested Citation

  • Yu, Bin & Yang, Zhong-Zhen & Yao, Baozhen, 2009. "An improved ant colony optimization for vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 196(1), pages 171-176, July.
    • Handle: RePEc:eee:ejores:v:196:y:2009:i:1:p:171-176
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    References listed on IDEAS

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    1. B. Bullnheimer & R.F. Hartl & C. Strauss, 1999. "An improved Ant System algorithm for theVehicle Routing Problem," Annals of Operations Research, Springer, vol. 89(0), pages 319-328, January.
    2. Brandao, Jose & Mercer, Alan, 1997. "A tabu search algorithm for the multi-trip vehicle routing and scheduling problem," European Journal of Operational Research, Elsevier, vol. 100(1), pages 180-191, July.
    3. Koulamas, C & Antony, SR & Jaen, R, 1994. "A survey of simulated annealing applications to operations research problems," Omega, Elsevier, vol. 22(1), pages 41-56, January.
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