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新冠疫情期间非接触式联合配送服务的车辆路径问题

Vehicle routing problem of contactless joint distribution service during COVID-19 pandemic.

作者信息

Chen Dawei, Pan Shuangli, Chen Qun, Liu Jiahui

机构信息

School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China.

出版信息

Transp Res Interdiscip Perspect. 2020 Nov;8:100233. doi: 10.1016/j.trip.2020.100233. Epub 2020 Oct 1.

Abstract

In order to prevent the further spread of the COVID-19 virus, enclosed management of gated communities is necessary. The implementation of contactless food distribution for closed gated communities is an urgent issue. This paper proposes a contactless joint distribution service to avoid contact between couriers. Then a multi-vehicle multi-trip routing problem for contactless joint distribution service is proposed, and a mathematical programming model for this problem is established. The goal of the model is to increase residents' satisfaction with food distribution services. To solve this model, a PEABCTS algorithm is developed, which is the enhanced artificial bee colony algorithm embedded with a tabu search operator, using a progressive method to form a solution of multi-vehicle distribution routings. Finally, a variety of numerical simulations were carried out for statistical research. Compared with the two distribution services of supportive supply and on-demand supply, the proposed contactless joint distribution service can not only improve residents' satisfaction with the distribution service but also reduce the contact frequency between couriers. In addition, compared with various algorithms, it is found that the PEABCTS algorithm has better performance.

摘要

为防止新冠病毒进一步传播,实行封闭小区的封闭式管理很有必要。为封闭小区实施无接触食品配送是一个亟待解决的问题。本文提出一种无接触联合配送服务,以避免快递员之间的接触。进而提出了无接触联合配送服务的多车辆多趟次路径规划问题,并建立了该问题的数学规划模型。该模型的目标是提高居民对食品配送服务的满意度。为求解该模型,开发了一种PEABCTS算法,即嵌入禁忌搜索算子的增强人工蜂群算法,采用递进方法形成多车辆配送路线的解决方案。最后进行了多种数值模拟以进行统计研究。与支持性供应和按需供应这两种配送服务相比,所提出的无接触联合配送服务不仅能提高居民对配送服务的满意度,还能降低快递员之间的接触频率。此外,与各种算法相比,发现PEABCTS算法具有更好的性能。

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本文引用的文献

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Artificial Bee Colony Algorithm Based on Information Learning.
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