O2O模式下外卖骑手的配送路径优化

靳志宏, 鞠新诚, 郭加佳, 杨珍花

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大连海事大学学报 ›› 2019, Vol. 45 ›› Issue (4) : 55-64. DOI: 10.16411/j.cnki.issn1006-7736.2019.04.008
交通运输工程

O2O模式下外卖骑手的配送路径优化

  • 靳志宏*1,鞠新诚1,郭加佳1,杨珍花2
作者信息 +

Optimization on distribution routes of the takeaway delivery staff under the O2O mode

  • JIN Zhi-hong*1, JU Xin-cheng1,GUO Jia-jia1,YANG Zhen-hua2
Author information +
History +

摘要

基于大连市某外卖配送站点的运营实例,针对午餐高峰时段涌入的大量订单,对骑手的配送路径进行优化.以最大化运输效率为目标,综合考虑外卖配送的实际约束,有针对性地构建骑手配送路径优化的混合整数规划模型,开发改进型蚁群算法对实例进行求解.然后,将所得结果与行业实际数据、小规模算例的CPLEX精确解以及传统的蚁群算法进行对比,从多方面验证了算法的合理性与有效性.最后,详细分析了算法参数对优化结果的影响机理,可为外卖配送行业提供决策支持.

Abstract

Based on the operation example of a takeaway distribution station in Dalian,  the distribution route of riders was optimized  for the influx of orders during the lunch rush hour. Aiming at maximizing transportation efficiency and by considering the actual constraints of takeout distribution, a mixed integer programming model for rider distribution route optimization was constructed, and an improved ant colony algorithm was developed to solve the case. Then the results were compared with the actual industry data, the CPLEX exact solution of the small-scale example and the traditional ant colony algorithm, the rationality and effectiveness of the algorithm were verified from many aspects. Finally, the influence mechanism of the algorithm parameters on the optimization results was analyzed in detail, which can provide decision support for takeout distribution industry.

关键词

O2O / 外卖 / 配送路径优化 / 取送货 / 蚁群算法

Key words

 on line to offline(O2O) / takeaway / distribution routing optimization / pickup and delivery / ant colony algorithm

引用本文

导出引用
靳志宏, 鞠新诚, 郭加佳, 杨珍花. O2O模式下外卖骑手的配送路径优化[J]. 大连海事大学学报, 2019, 45(4): 55-64. https://doi.org/10.16411/j.cnki.issn1006-7736.2019.04.008
JIN Zhi-hong, JU Xin-cheng, GUO Jia-jia, YANG Zhen-hua. Optimization on distribution routes of the takeaway delivery staff under the O2O mode[J]. Journal of Dalian Maritime University, 2019, 45(4): 55-64. https://doi.org/10.16411/j.cnki.issn1006-7736.2019.04.008

参考文献

[1]Dantzig G B, Ramser J H.The truck dispatching problem[J].Management Science, 1959, 6(1):80-91
[2]吴腾宇, 陈嘉俊, 蹇洁.模式下的配送车辆实时取送货路径选择问题[J].系统工程理论与实践, 2018, 38(11):2885-2891
[3]张庆华, 吕小丹.电商退换货车辆路径问题及蚁群算法研究[J].计算机工程与应用, 2018, 54(22):239-245
[4]Marilène C, Guy D, Stefan I, Gilbert L.Branch-price-and-cut algorithms for the pickup and delivery problem with time windows and multiple stacks[J].European Journal of Operational Research, 2015, 250(1):782-793
[5]Chávez M A C, Martinez-Oropeza A.Feasible initial population with genetic diversity for a population-based algorithm applied to the vehicle routing problem with time windows[J]. Mathematical Problems in Engineering, 2016(5): 1-11.
[6]Inmaculada R M, Juan-José S G, Hande Y.The periodic vehicle routing problem with driver consistency[J].European Journal of Operational Research, 2018, 273(1):575-584
[7]Armando H P, Sebastián U.Formulations and algorithms for the pickup and delivery traveling salesman problem with multiple stacks[J].Computers and Operations Research, 2018, 93(1):1-14
[8]王帅, 赵来军, 胡青蜜.随机旅行时间的外卖 配送车辆路径问题[J].物流科技, 2017, 40(1):93-101
[9]陈萍, 李航.基于时间满意度的 外卖配送路径优化问题研究[J].中国管理科学, 2016, SI(24):171-176
[10]陈希琼, 胡大伟, 杨倩倩, 胡卉, 高扬.多目标同时取送货车辆路径问题的改进蚁群算法[J].控制理论与应用, 2018, 35(09):1347-1356
[11]柴获, 何瑞春, 苏江省, 宋宇博, 代存杰, 马昌喜.求解双目标带时间窗车辆路径问题的蚁群算法[J].交通运输系统工程与信息, 2018, 18(4):156-162
[12]裴振兵, 陈雪波.改进蚁群算法及在车辆运输调度中的应用[J].信息与控制, 2015, 44(6):753-758
[13]杨鹏, 邹浩, 徐贤浩.带时间窗集送货需求可分车辆路径问题的改进蚁群算法[J].系统工程, 2015, 33(9):58-62
[14]Schyns M.An ant colony system for responsive dynamic vehicle routing[J].European Journal of Operational Research, 2015, 245(3):704-718
[15] Caporossi G, Hansen P, Nenad Mladenovi?.Variable Neighborhood Search[M]. Elsevier Science Ltd. 1997.

基金

国家自然科学基金面上项目(71572023;71702019);欧盟H2020项目(MSCA-RISE 777742-56);大连市领军人才项目(2018-573);中央高校基本科研业务费专项资金资助项目(3132019301;3132019031).
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