Gialos Anastasios, Zeimpekis Vasileios
Design Operations and Production Systems Lab, Department of Financial & Management Engineering, School of Engineering, University of the Aegean, 41 Kountouriotou Street, 82100, Chios, Greece.
Data Brief. 2023 Aug 1;50:109464. doi: 10.1016/j.dib.2023.109464. eCollection 2023 Oct.
Regarding climate change and energy resource problems, cargo movement in the urban environment is essential to shift to a more sustainable mode. As cities seek to slash transport-related emissions and tackle traffic congestion, the cargo bike is showing itself to be an attractive and versatile last-mile delivery alternative. To this end, this article presents a series of datasets for the Electric Capacitated Travelling Salesman Problem (EC-TSP). This problem has been built for modeling and solving the e-cargo bike parcel distribution problem in urban environments. For the design of these datasets, real geographical data have been used that are in the city centers of Athens, Thessaloniki, Patra, and Larisa in Greece. These datasets have been used for the assessment of e-cargo bikes versus typical delivery vans in terms of operational efficiency and COe emissions. The entire benchmark is composed of 9 instances comprised of 14-29 nodes each. The datasets are publicly available for use and modification.
关于气候变化和能源资源问题，城市环境中的货物运输向更可持续模式转变至关重要。随着城市努力削减与交通相关的排放并解决交通拥堵问题，货运自行车正展现出自身是一种有吸引力且用途广泛的最后一英里配送选择。为此，本文提出了一系列用于电容式电动旅行商问题（EC-TSP）的数据集。该问题是为模拟和解决城市环境中的电动货运自行车包裹配送问题而构建的。在设计这些数据集时，使用了希腊雅典、塞萨洛尼基、帕特雷和拉里萨市中心的真实地理数据。这些数据集已用于评估电动货运自行车与典型送货车在运营效率和二氧化碳排放方面的情况。整个基准由9个实例组成，每个实例包含14 - 29个节点。这些数据集可供公众使用和修改。
