Minimizing urban logistics cost using crowd-shipping

Over the years, many researchers have extended VRP, with the aim of shortening total mileage, reduce costs and optimize vehicle capacity. This study aims to determine the method of a crowd-shipping that can reduce shipping costs. The proposed model is an extension of the classical VRP method. In its application this model involves ordinary people for the delivery process. The CSVRP model is divided into two. The first model changes in fixed price and the other models with changes in variable price. This model is tested using data from one of the logistics companies in Bandung, Indonesia. Both models show quite good results, where shipping costs for CSVRP with Fixed Price can be reduced by 33% also CSVRP with Variable Price can be reduced by 39% . In addition, the calculation of carbon dioxide emissions is also a consideration for both models. The output produced from the two models is also quite good, because at least 46% of carbon dioxide emissions can be reduced. Overall, this research has the potential both in economic scope and also in environmental sustainability.多年来，诸多研究者对车辆路径问题（Vehicle Routing Problem，VRP）进行拓展，旨在缩短总行驶里程、降低成本并优化车辆装载能力。本研究旨在探寻可降低物流成本的众包物流（crowd-shipping）实施方案。所提出的模型是经典VRP的拓展版本，其应用过程中会吸纳普通民众参与配送流程。众包物流车辆路径问题（Crowd-shipping Vehicle Routing Problem，CSVRP）模型分为两类：第一类采用固定定价机制，第二类采用可变定价机制。本研究采用印度尼西亚万隆市某物流公司的数据集对该模型进行测试。两类模型均取得了优异的测试效果：采用固定定价的CSVRP可将物流成本降低33%，采用可变定价的CSVRP则可降低39%。此外，两类模型均将二氧化碳排放量测算纳入考量范畴。两类模型的输出表现同样出色，可实现至少46%的二氧化碳减排量。总体而言，本研究在经济效益与环境可持续性两方面均具备可观的应用潜力。