城市物流配送的混合车辆路径规划模型与优化算法研究
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湖南工商大学

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C93

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国家自然科学基金项目(面上项目,重点项目,重大项目)


Research on Programming Model and Optimization Algorithm for the Mixed Fleet Vehicle Routing Problem in Urban Logistics Distribution
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Hunan University of Business and Technology

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    摘要:

    针对城市部分区域限行、物流系统中燃油车与电动车同时并存的实际情况,综合考虑客户需求量、服务时间、电动车行驶里程、已有充电设施、部分充电策略、燃油车油耗与碳排放等因素,以车辆使用固定成本、驾驶员工资、电动车的充电成本、燃油车的油耗与碳排放成本之和最小为目标构建混合车辆路径规划模型;根据模型特征设计一种改进蚁群算法求解,并采用多类型算例进行实验,实验结果表明本文方法能在非常短的时间内给出符合决策者目标的混合车辆路径规划方案,有效降低总配送成本,减少燃油车油耗与碳排放,具有合理性、可行性与有效性。

    Abstract:

    Aiming at the actual situation of regional restrictions in some urban areas and the coexistence of fuel vehicles and electric vehicles in the logistics system, a programming model of the mixed fleet vehicle routing problem (MFVRP) is formulated by comprehensively considering the factors such as customer demand, service time, electric vehicles range, existing charging facilities, partial charging strategy, vehicle fuel consumption and carbon emissions. The goal of the MFVRP model is to minimize the sum of fixed cost of vehicles, driver salary, charging cost of electric vehicles, cost of fuel consumption and carbon emissions. An improved ant colony algorithm was designed to solve the problem according to the characteristics of the MFVRP model. The experiments were carried out with multiple types of instances. The experimental results show that the proposed methods can provide a satisfactory MFVRP solution that meets the goal of decision makers in very short time, effectively reduce the total distribution cost, reduce fuel consumption and carbon emissions. The proposed approaches are reasonable, feasible and effective.

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历史
  • 收稿日期:2021-08-18
  • 最后修改日期:2022-01-11
  • 录用日期:2022-01-11
  • 在线发布日期: 2022-02-01
  • 出版日期: