This paper addresses the open vehicle routing problem with time window(OVRPTW), where each vehicle does not need to return to the depot after completing the delivery task.The optimization objective is to minimize the ...This paper addresses the open vehicle routing problem with time window(OVRPTW), where each vehicle does not need to return to the depot after completing the delivery task.The optimization objective is to minimize the total distance. This problem exists widely in real-life logistics distribution process.We propose a hybrid column generation algorithm(HCGA) for the OVRPTW, embedding both exact algorithm and metaheuristic. In HCGA, a label setting algorithm and an intelligent algorithm are designed to select columns from small and large subproblems, respectively. Moreover, a branch strategy is devised to generate the final feasible solution for the OVRPTW. The computational results show that the proposed algorithm has faster speed and can obtain the approximate optimal solution of the problem with 100 customers in a reasonable time.展开更多
This paper proposes a solution to the open vehicle routing problem with time windows(OVRPTW)considering third-party logistics(3PL).For the typical OVRPTW problem,most researchers consider time windows,capacity,routing...This paper proposes a solution to the open vehicle routing problem with time windows(OVRPTW)considering third-party logistics(3PL).For the typical OVRPTW problem,most researchers consider time windows,capacity,routing limitations,vehicle destination,etc.Most researchers who previously investigated this problem assumed the vehicle would not return to the depot,but did not consider its final destination.However,by considering 3PL in the B2B e-commerce,the vehicle is required back to the nearest 3PL location with available space.This paper formulates the problem as a mixed integer linear programming(MILP)model with the objective of minimizing the total travel distance.A coordinate representation particle swarm optimization(CRPSO)algorithm is developed to obtain the best delivery sequencing and the capacity of each vehicle.Results of the computational study show that the proposed method provides solution within a reasonable amount of time.Finally,the result compared to PSO also indicates that the CRPSO is effective.展开更多
针对电商企业开放式物流配送路径优化问题,考虑车辆使用成本、运输成本以及碳排放成本,建立企业满意度模型,考虑顾客的多个模糊时间窗口建立顾客满意度模型,将二者综合,构建了基于企业与顾客综合满意度的开放式电商物流车辆路径优化模型...针对电商企业开放式物流配送路径优化问题,考虑车辆使用成本、运输成本以及碳排放成本,建立企业满意度模型,考虑顾客的多个模糊时间窗口建立顾客满意度模型,将二者综合,构建了基于企业与顾客综合满意度的开放式电商物流车辆路径优化模型(Open vehicle routing problem-the model based on comprehensive satisfaction of enterprises and customers,OVRP-CSEC),并结合早晚高峰交通状况分析车辆时变速度与行驶时间。设计“自适应-邻域搜索蚁群算法”(Adaptive-neighborhood search ant colony optimization,A-NACO),对蚁群算法的状态转移概率,信息素更新策略进行改进,并在算法中加入大邻域搜索机制以增强算法的搜索性能。采用实际案例与改进的Solomon测试算例,设计两组对比实验,验证了模型及算法在综合与提高电商企业与顾客满意度、降低物流配送成本上的有效性。展开更多
基金supported by the National Natural Science Foundation of China (61963022,51665025,61873328)。
文摘This paper addresses the open vehicle routing problem with time window(OVRPTW), where each vehicle does not need to return to the depot after completing the delivery task.The optimization objective is to minimize the total distance. This problem exists widely in real-life logistics distribution process.We propose a hybrid column generation algorithm(HCGA) for the OVRPTW, embedding both exact algorithm and metaheuristic. In HCGA, a label setting algorithm and an intelligent algorithm are designed to select columns from small and large subproblems, respectively. Moreover, a branch strategy is devised to generate the final feasible solution for the OVRPTW. The computational results show that the proposed algorithm has faster speed and can obtain the approximate optimal solution of the problem with 100 customers in a reasonable time.
文摘This paper proposes a solution to the open vehicle routing problem with time windows(OVRPTW)considering third-party logistics(3PL).For the typical OVRPTW problem,most researchers consider time windows,capacity,routing limitations,vehicle destination,etc.Most researchers who previously investigated this problem assumed the vehicle would not return to the depot,but did not consider its final destination.However,by considering 3PL in the B2B e-commerce,the vehicle is required back to the nearest 3PL location with available space.This paper formulates the problem as a mixed integer linear programming(MILP)model with the objective of minimizing the total travel distance.A coordinate representation particle swarm optimization(CRPSO)algorithm is developed to obtain the best delivery sequencing and the capacity of each vehicle.Results of the computational study show that the proposed method provides solution within a reasonable amount of time.Finally,the result compared to PSO also indicates that the CRPSO is effective.
文摘针对电商企业开放式物流配送路径优化问题,考虑车辆使用成本、运输成本以及碳排放成本,建立企业满意度模型,考虑顾客的多个模糊时间窗口建立顾客满意度模型,将二者综合,构建了基于企业与顾客综合满意度的开放式电商物流车辆路径优化模型(Open vehicle routing problem-the model based on comprehensive satisfaction of enterprises and customers,OVRP-CSEC),并结合早晚高峰交通状况分析车辆时变速度与行驶时间。设计“自适应-邻域搜索蚁群算法”(Adaptive-neighborhood search ant colony optimization,A-NACO),对蚁群算法的状态转移概率,信息素更新策略进行改进,并在算法中加入大邻域搜索机制以增强算法的搜索性能。采用实际案例与改进的Solomon测试算例,设计两组对比实验,验证了模型及算法在综合与提高电商企业与顾客满意度、降低物流配送成本上的有效性。
