4.7 Article

Research on the Time-Dependent Split Delivery Green Vehicle Routing Problem for Fresh Agricultural Products with Multiple Time Windows

期刊

AGRICULTURE-BASEL
卷 12, 期 6, 页码 -

出版社

MDPI
DOI: 10.3390/agriculture12060793

关键词

vehicle routing problem; fresh agricultural products; split delivery; NSGA-II algorithm

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资金

  1. China Education Ministry of Humanities and Social Science Research Youth Fund project [18YJCZH192]
  2. Applied Undergraduate Pilot Project for Logistics Management of Shanghai Ocean University
  3. Open Project Program of Artificial Intelligence Key Laboratory of Sichuan province [2015RYJ01]
  4. Social Science Project in Hunan province [16YBA316]

向作者/读者索取更多资源

This paper studies the last mile split delivery problem of agricultural products, considering economic cost and customer satisfaction. It proposes a method for calculating road travel time across time periods and measures satisfaction based on time windows and economic cost. The proposed approach effectively reduces costs, promotes energy conservation, and improves customer satisfaction.
Due to the diversity and the different distribution conditions of agricultural products, split delivery plays an important role in the last mile distribution of agricultural products distribution. The time-dependent split delivery green vehicle routing problem with multiple time windows (TDSDGVRPMTW) is studied by considering both economic cost and customer satisfaction. A calculation method for road travel time across time periods was designed. A satisfaction measure function based on a time window and a measure function of the economic cost was employed by considering time-varying vehicle speeds, fuel consumption, carbon emissions and customers' time windows. The object of the TDSDGVRPMTW model is to minimize the sum of the economic cost and maximize average customer satisfaction. According to the characteristics of the model, a variable neighborhood search combined with a non-dominated sorting genetic algorithm II (VNS-NSGA-II) was designed. Finally, the experimental data show that the proposed approaches effectively reduce total distribution costs and promote energy conservation and customer satisfaction.

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