货运O2O平台有时间窗同城零担集货匹配优化决策

零担集货业务的供需匹配和路线规划问题是同城货运020平台面临的发展难点.本文站在平台的角度,同时考虑司机和客户的实际需求,引入单位订单处理时间窗的概念,提出操作性较强的零担集货预匹配优化策略,突破传统逐级推送模式的思维局限,充分考虑需求和运力的属性-时间-空间分布;其次综合考虑客户OD点对、订单时间窗、以及司机工作时间窗、起终点、车辆容量限制等因素,在不考虑拒绝订单的条件下,以最小化服务总成本为优化目标,构建单位订单处理时间窗内某区域的半开放式多车场的带取送货和时间窗的车辆路径优化模型.最后针对模型特性采用改进的遗传算法进行求解,并选取卓集送公司某市某区某单位订单处理时间段(高峰期)连续60天的实例数据进行实证分析.研究结果表明,改进遗传算法的求解质量明显高于就近匹配贪婪算法,优化比例平均值为30%,最高达到53%,从而实现司机和客户双方的利益最大化.

Matching optimization decision of city LTL carpool based on time windows on the freight O2O platform

The majority of the freight O2O platforms are faced with the difficulties that matching supply and demand and planning routes in the development of LTL (less-than-truckload, LTL) carpool system. This paper simultaneously considers the demand of drivers and clients on platform's side to propose the optimized pre-matching policy which introduces the unit order-processing time window, breaking through the limitation of traditional "step by step pushing mode" and comprehensively considering the attribute-time-space distribution of demand and capacity. Then under the premise of considering the factors of clients' OD points, time windows and drivers' working time windows, start-end terminals and vehicle capacity, we construct the mathematical model which called the half-open multi-depot vehicle routing problem with pick-up and delivery and time windows, aiming at minimizing the total cost and without rejecting orders. Finally, we use the improved genetic algorithm to solve it based on its features, selecting the practical data of Zallsoon during the peak period (for 60 days) in a certain distinct to confirm the superiority and feasibility. The obtained results illustrate that improved genetic algorithm (comparing with "closely-matching greedy algorithm") can significantly reduce the total service cost by an average of 30% (up to 53%) and realize the maximization of interests of drivers and clients.