Vehicle Routing Problem with Private fleet and common Carrier (VRPPC) has been proposed to help a supplier manage package delivery services from a single depot to multiple customers. Most of the existing VRPPC works consider deterministic parameters which may not be practical and uncertainty has to be taken into account. In this paper, we propose the Optimal Stochastic Delivery Planning with Deadline (ODPD) to help a supplier plan and optimize the package delivery. The aim of ODPD is to service all customers within a given deadline while considering the randomness in customer demands and traveling time. We formulate the ODPD as a stochastic integer programming, and use the cardinality minimization approach for calculating the deadline violation probability. To accelerate computation, the L-shaped decomposition method is adopted. We conduct extensive performance evaluation based on real customer locations and traveling time from Google Map.
翻译:提议由私人车队和普通运输公司(VRPPC)处理车辆问题,以帮助供应商管理从一个仓库到多个客户的包件交付服务; 现有的VRPPC大部分工作考虑可能不切实际的确定性参数,必须考虑到不确定因素; 本文提出最佳托盘交付计划,以帮助供应商计划,优化包件交付; ODPD的目的是在一定的最后期限内为所有客户提供服务,同时考虑客户需求和旅行时间的随机性; 我们把ODPD设计成一个随机的整数程序,并采用最基本化的方法计算违反最后期限的概率; 为了加速计算,我们采用了L形分解法; 我们根据实际客户地点和谷歌地图的旅行时间进行广泛的业绩评估。