期刊
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
卷 -, 期 -, 页码 -出版社
SPRINGER
DOI: 10.1007/s10668-022-02604-z
关键词
Supply chain network; Multi-objective model; Mixed-integer linear programming; Robust optimization; COVID-19 outbreak
This study proposes a flexible optimization model to establish a robust mask supply chain network under uncertainty. The model's applicability is demonstrated for the Greater Toronto Area in Canada, where medical supply producers were encouraged to switch their operations to produce masks.
Wearing a mask or a face covering became mandatory in indoor public spaces to reduce the spread of coronavirus disease 2019 (COVID-19). The Ontario government (i.e., a province of Canada) encouraged medical supply producers to switch their operations to produce personal protective equipment (e.g., masks) during the COVID-19 pandemic. In this regard, there are several uncertain parameters (e.g., operational costs, market demand, and capacity levels of facilities) affecting the performance of producers in a medical supplies market. In this study, we propose a flexible optimization model to configure a robust mask supply chain network under uncertainty. Furthermore, companies are supposed to undertake their operations based on sustainable manners, in compliance with provincial policy, in Ontario. Therefore, the proposed flexible optimization model is extended to a robust multi-objective model to investigate sustainable strategies in a mask supply chain network design problem. The applicability of this model is demonstrated for the Greater Toronto Area, Canada.
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