Design and optimization of a sustainable and resilient mask supply chain during the COVID-19 pandemic: A multi-objective approach

Abstract

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.

Robust design of a logistics system using FePIA procedure and analysis of trade-offs between CO2 emissions and net present value

“…Recently, multi-objective sustainable supply chain design problems have been studied by Refs. [ 107 , 108 ]. Alizadeh-Meghrazi et al [ 107 ] proposed a robust multi-objective model to study sustainable methods for a mask supply chain network design.…”

“…[ 107 , 108 ]. Alizadeh-Meghrazi et al [ 107 ] proposed a robust multi-objective model to study sustainable methods for a mask supply chain network design. This model's applicability is illustrated for Canada's Greater Toronto Area.…”