Crowd-shipping problem with time windows, transshipment nodes, and delivery options

转运(资讯保安) 车辆路径问题 解算器 灵活性(工程) 计算机科学 最后一英里(运输) 运筹学 集合(抽象数据类型) 过程(计算) 交付性能 数学优化 布线(电子设计自动化) 运输工程 工程类 数学 计算机网络 工业工程 英里 程序设计语言 物理 操作系统 统计 天文
作者
Vincent F. Yu,Panca Jodiawan,Anak Agung Ngurah Perwira Redi
出处
期刊:Transportation Research Part E-logistics and Transportation Review [Elsevier BV]
卷期号:157: 102545-102545 被引量:38
标识
DOI:10.1016/j.tre.2021.102545
摘要

This research introduces a new variant of the vehicle routing problem in the last-mile delivery process - namely, the Crowd-Shipping Problem with Time Windows, Transshipment Nodes, and Delivery Options (CSPTW-TN-DO). Two types of fleets (i.e., dedicated vehicles and occasional drivers) are available to serve three types of customers. Type 1 customers require a home delivery. The parcel of type 2 customers must be sent to the selected alternative delivery point (ADP). Type 3 customers have the flexibility to either receive their parcel at home or at the selected ADP. Dedicated vehicles are able to serve all types of customers, whereas occasional drivers only make home deliveries. The objective of CSPTW-TN-DO is to minimize the total distribution cost of employing both fleets. We formulate a Mixed Integer Nonlinear Programming (MINLP) model for the problem and solve the model by the commercial solver CPLEX after applying a linearization process. We also propose an Adaptive Large Neighborhood Search (ALNS) to solve a set of newly generated CSPTW-TN-DO instances. The computational results indicate that the proposed ALNS provides high-quality solutions. In addition, we show that the VRPTW with a primary objective of minimizing the total distribution cost is a special case of CSPTW-TN-DO, and that the proposed ALNS achieves comparative performance to the state-of-the-art algorithms for VRPTW. After analyzing several scenarios, we conclude that simultaneously considering occasional drivers, transshipment nodes, and delivery options offers a great opportunity for a last-mile delivery system to reduce its total distribution cost.

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