期刊
APPLIED SCIENCES-BASEL
卷 13, 期 12, 页码 -出版社
MDPI
DOI: 10.3390/app13127259
关键词
last-mile delivery; urban logistics; vehicle routing; sustainability; river logistic
This research proposes a multimodal alternative for last-mile delivery using a barge and two sustainable network designs. The efficiency of the scenarios is assessed using performance indicators and a three-stage decomposition heuristic method. The allocation of customers is done using a non-supervised clustering method in the first stage, followed by a heuristic based on the nearest neighbor procedure for routing in the next two stages. The application of river transportation and e-cargo bikes results in a significant reduction in fixed costs and energy consumption.
Studies that use rivers in a last-mile delivery context are scarce. This research considers the first multimodal alternative based on a barge for parcel delivery activities. It proposes two sustainable network designs for a two-echelon distribution. The efficiency of scenarios is assessed through performance indicators. A three-stage decomposition heuristic is used. Allocation of the customers to the closest satellite at the first stage uses a non-supervised machine learning clustering method, 2D-k-means. The last two stages, comprising the two echelons routing, are solved using a heuristic based on the nearest neighbor procedure. The fixed costs decrease by 41% and energy consumption by 92% when applying a river transportation mode and e-cargo bikes in the distribution network's first and second echelon, respectively. Future research avenues are to render the results more realistic with the consideration of other costs and a larger network.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据