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基于安全距离的车辆路径规划问题:新冠疫情期间医疗废物收集案例研究

Safe distance-based vehicle routing problem: Medical waste collection case study in COVID-19 pandemic.

作者信息

Eren Emre, Rıfat Tuzkaya Umut

机构信息

Department of Industrial Engineering, Faculty of Engineering and Architecture, University of Beykent, Turkey.

Department of Industrial Engineering, Faculty of Mechanical, University of Yıldız Teknik, Barbaros Avenue, PO Box: 34349, Besiktas, Istanbul, Turkey.

出版信息

Comput Ind Eng. 2021 Jul;157:107328. doi: 10.1016/j.cie.2021.107328. Epub 2021 Apr 16.

Abstract

In addition to the increasing population and rapid urbanization, the amount and variety of medical waste are rapidly increasing due to the coronavirus disease (COVID-19) pandemic affecting the whole world. COVID-19 does not only increase the amount of medical waste produced, medical wastes generated in the care of COVID-19 carries a high risk of transmission as well. In this regard, the safe and effective management of medical wastes has become a serious health and safety issue. This research aims to determine the safest and shortest transportation routes for medical waste vehicles. The safety scores used in this study were obtained in our previous study. The resulting safety scores were used in a multi-objective traveling salesman problem for deriving two objective functions, which are based on safety scores and total transportation distance. A conciliating solution was obtained by solving this linear programming model. The proposed model faced by health institutions in Istanbul has been applied for a specific district. According to the obtained results, suggestions for the direction of medical waste vehicles have been proposed.

摘要

除了人口增长和快速城市化外,由于影响全球的冠状病毒病(COVID-19)大流行,医疗废物的数量和种类也在迅速增加。COVID-19不仅增加了产生的医疗废物数量,在COVID-19护理过程中产生的医疗废物还具有很高的传播风险。在这方面,医疗废物的安全有效管理已成为一个严重的健康和安全问题。本研究旨在确定医疗废物运输车辆最安全、最短的运输路线。本研究中使用的安全分数是在我们之前的研究中获得的。所得安全分数用于多目标旅行商问题,以推导基于安全分数和总运输距离的两个目标函数。通过求解该线性规划模型获得了一个折衷解。伊斯坦布尔的卫生机构面临的该模型已应用于一个特定地区。根据所得结果,提出了医疗废物运输车辆行驶方向的建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3034/8051006/b16e583e76c7/gr1_lrg.jpg

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