Maximum Profit Facility Location and Dynamic Resource Allocation for Instant Delivery Logistics
Maximum Profit Facility Location and Dynamic Resource Allocation for Instant Delivery Logistics
复制标题
DOI：
10.1177/03611981221082574
复制
发表时间：
2022-03
影响因子：
1.7
通讯作者：
Darshan Rajesh Chauhan;A. Unnikrishnan;S. Boyles
中科院分区：
文献类型：
--
作者：
Darshan Rajesh Chauhan;A. Unnikrishnan;S. Boyles
电子商务活动的增加、缩短交货时间的竞争以及运输技术的创新推动了该行业走向即时交货物流。本文研究了一个设施定位和在线需求分配问题，适用于物流公司扩展到提供即时交付服务，使用无人机或无人机。问题被分解为两个阶段。在规划阶段，确定设施的位置，并分配产品和电池容量。在运营阶段，客户动态下订单，实时需求分配决策。本文探讨了一个多臂强盗框架，以最大限度地提高物流公司实现的累积回报，受到各种能力的限制，并与其他战略进行了比较。在标准测试实例上测试时，多臂强盗框架提供的奖励比第二好的策略多7%。基于波特兰都会区的案例研究表明，多武装匪徒可以超过第二个最好的战略超过20%。
Increasing e-commerce activity, competition for shorter delivery times, and innovations in transportation technologies have pushed the industry toward instant delivery logistics. This paper studies a facility location and online demand allocation problem applicable to a logistics company expanding to offer instant delivery service using unmanned aerial vehicles or drones. The problem is decomposed into two stages. During the planning stage, the facilities are located, and product and battery capacity are allocated. During the operational stage, customers place orders dynamically and real-time demand allocation decisions are made. The paper explores a multi-armed bandit framework for maximizing the cumulative reward realized by the logistics company subject to various capacity constraints and compares it with other strategies. The multi-armed bandit framework provides about 7% more rewards than the second-best strategy when tested on standard test instances. A case study based in Portland Metro Area showed that multi-armed bandits can outperform the second-best strategy by more than 20%.