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Fresh seafood delivery routing problem using an improved ant colony optimization

Author

Listed:
  • Baozhen Yao

    (Dalian University of Technology)

  • Chao Chen

    (Dalian University of Technology)

  • Xiaolin Song

    (Dalian Maritime University)

  • Xiaoli Yang

    (Dalian Maritime University)

Abstract

Energy cost for keeping fresh seafood in cold condition is a main feature of a fresh seafood delivery routing problem. In the delivery routing problem, energy cost varies during the transportation process and the service process. In addition, there are many fresh seafood product factories whose seafood products should be delivered to a set of customers. Therefore, this paper models the fresh seafood delivery problem as a multi-depot vehicle routing problem, which aims to find the routes with the least cost. Due to the complexity of the problem, a method is used to reduce the complexity by changing the multi-depot vehicle routing problem into a vehicle routing problem with a dummy depot in this paper. Then, ant colony optimization (ACO) is used to solve this problem. Scanning strategy and crossover operation are also adopted to improve the performance of ACO. At last, the computational results of the benchmark problems of the multi-depot vehicle routing problem indicate the effectiveness of the algorithm. Furthermore, the real-life fresh seafood delivery routing problem from Dalian city suggests the proposed model is feasible.

Suggested Citation

  • Baozhen Yao & Chao Chen & Xiaolin Song & Xiaoli Yang, 2019. "Fresh seafood delivery routing problem using an improved ant colony optimization," Annals of Operations Research, Springer, vol. 273(1), pages 163-186, February.
    • Handle: RePEc:spr:annopr:v:273:y:2019:i:1:d:10.1007_s10479-017-2531-2
    DOI: 10.1007/s10479-017-2531-2
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    2. Daqing Wu & Chenxiang Wu, 2022. "Research on the Time-Dependent Split Delivery Green Vehicle Routing Problem for Fresh Agricultural Products with Multiple Time Windows," Agriculture, MDPI, vol. 12(6), pages 1-28, May.
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