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A Study of Community Group Purchasing Vehicle Routing Problems Considering Service Time Windows

Author

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  • Wei Song

    (School of Marxism, Xidian University, Xi’an 710071, China)

  • Shuailei Yuan

    (School of Economics and Management, Xidian University, Xi’an 710071, China)

  • Yun Yang

    (School of Economics and Management, Xidian University, Xi’an 710071, China)

  • Chufeng He

    (School of Economics and Management, Xidian University, Xi’an 710071, China)

Abstract

In this paper, a vehicle routing problem (VRP) model considering delivery time windows and variable service time is established for the delivery problem in community group purchasing. A solution model for an improved ant colony algorithm (ACA) is proposed by improving the initial feasible solution and the neighbourhood search mechanism of the ant colony algorithm. The algorithm of the improved ant colony and the commonly used algorithm are solved for real cases and publicly available benchmark datasets, respectively, for comparative analysis. The results show that the improved ACA has stronger optimization capability, faster convergence speed, and has advantages in solving VRPTW problems with variable service time. The computational efficiency is also improved by 41% over the genetic algorithm (GA) in the solution of the benchmark dataset, which provides a certain reference for solving the community group distribution problem.

Suggested Citation

  • Wei Song & Shuailei Yuan & Yun Yang & Chufeng He, 2022. "A Study of Community Group Purchasing Vehicle Routing Problems Considering Service Time Windows," Sustainability, MDPI, vol. 14(12), pages 1-17, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:12:p:6968-:d:833193
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    References listed on IDEAS

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    Cited by:

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    2. Zhiqiang Liu & Yanqi Niu & Caiyun Guo & Shitong Jia, 2023. "A Vehicle Routing Optimization Model for Community Group Buying Considering Carbon Emissions and Total Distribution Costs," Energies, MDPI, vol. 16(2), pages 1-20, January.
    3. Daqing Wu & Rong Yan & Hongtao Jin & Fengmao Cai, 2023. "An Adaptive Nutcracker Optimization Approach for Distribution of Fresh Agricultural Products with Dynamic Demands," Agriculture, MDPI, vol. 13(7), pages 1-21, July.

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