通过考虑顾客偏好时间窗口的优化配送网络,最小化最后一英里配送成本和车辆使用量

G.Kasuri Abhilashani, M. Ranathunga, A. Wijayanayake
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摘要

在充满活力和发展的电子商务时代,最后一英里配送已成为其中的关键业务之一。由于持续的经济危机导致燃料和其他运营成本的增加,电子商务行业的最后一英里配送面临着高成本。为了克服这种情况,电子商务行业需要根据时间窗口优化车辆配送路线,以最大限度地降低总成本。尽管有许多关于最后一英里配送的研究,但考虑到客户预期的时间窗口,关于最后一英里配送优化的研究很少。因此,本研究的目的是在满足一些实际要求的同时,优化和最小化最后一英里配送作业的运输成本和车辆使用量,如多种包装类型,不同类型车辆的包装兼容性;客户期望的交付时间窗口和不同种类的车队。经过仔细的文献回顾,本文介绍了优化最后一英里配送的数学模型。在SupplyChainGuru®建模和仿真软件中对所提出的数学模型进行了仿真。该研究的结论是,在减少路线上的车辆数量、失败的包裹数量和最大限度地利用车辆容量的同时,将最后一英里的总体配送成本降至最低约22%,同时,通过让消费者有机会选择客户喜欢的包裹投递时间窗口,也提高了客户满意度。这种基于集群的交付将改善电子商务物流供应链的路线,并将作为一个平台,将基于集群的交付过程扩展到其他行业。
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Minimising Last-Mile Delivery Cost and Vehicle Usage Through an Optimised Delivery Network Considering Customer-Preferred Time Windows
In the dynamic and developing e-commerce era, last-mile delivery has emerged as one of the critical operations among all. The last-mile delivery in the e-commerce industry is facing high costs due to a going economic crisis which led to fuel and other operating cost increments. To overcome this situation, the e-commerce industry needs to optimise vehicle delivery routing based on time windows to minimise the overall cost. Despite numerous studies on last-mile delivery, there is a paucity of studies on last-mile delivery optimisation considering the customer’s anticipated time windows. Therefore, this study has been conducted with the objective of optimising and minimising transportation costs and vehicle usage in last-mile delivery operations while meeting some practical requirements such as a variety of package types, package compatibility on different types of vehicles; the customer expected delivery time windows and a heterogeneous fleet of vehicles. After a careful literature review, this paper introduces a mathematical model to optimise last-mile delivery. The proposed mathematical model was simulated in SupplyChainGuru® modelling and simulation software. The study concluded that the overall last-mile delivery cost is minimised by about 22% while reducing the number of vehicles on the route, failed delivery package count and utilising the maximum possible capacity of vehicles while also increasing customer satisfaction by giving consumers a chance to select customer preferred time windows for package delivery. This cluster-based delivery will improve the routing of the e-commerce logistic supply chain and will serve as a platform for extending the cluster-based delivery process to other industries as well.
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