文章基本信息

标题：Coordinated Ambulance Routing Problem for COVID-19 by Using Cloud-Theory-based Simulated Annealing to Minimize Number of Unserved Patients and Total Travel Distance
本地全文：下载
作者：Purba Daru Kusuma ; Ratna Astuti Nugrahaeni ; Dimas Adiputra 等
期刊名称：Engineering Letters
印刷版ISSN：1816-093X
电子版ISSN：1816-0948
出版年度：2022
卷号：30
期号：3
页码：955-963
语种：English
出版社：Newswood Ltd
摘要：This work proposes a new coordinated ambulance routing model suitable for implementation during the COVID19 pandemic. This model is different from the existing model, where it was conducted uncoordinatedly, so that mismatch between supply and demand may occur. In general, high number of unserved requests and travel distance are unwanted. Therefore, this work proposes a model consisting of three steps: hospital-patient allocation, ambulance-patient dispatching, and ambulance pickup-delivery sequencing. The proposed model consists of two objectives: minimizing the number of unserved patients and minimizing total travel distance. It is developed by using cloud-theory-based simulated annealing. The simulation result shows that the proposed model outperforms the existing uncoordinated model in number of unserved patients, total travel distance, and average travel distance. It creates zero unserved patients if the total number of patients does not surpass the total number of slots in all hospitals. It produces 12 to 19 percent lower total travel distance and 27 to 29 percent lower average travel distance than the uncoordinated model.
关键词：ambulance routing problem;COVID-19;metaheuristic;simulated annealing