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

Milad Alizadeh-Meghrazi, Babak Mohamadpour Tosarkani (), Saman Hassanzadeh Amin, Milos R Popovic and Payman Ahi
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Milad Alizadeh-Meghrazi: University of Toronto
Babak Mohamadpour Tosarkani: University of British Columbia, Okanagan Campus
Saman Hassanzadeh Amin: Toronto Metropolitan University
Milos R Popovic: University of Toronto
Payman Ahi: Toronto Metropolitan University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2025, vol. 27, issue 9, No 72, 22217-22262

Abstract: 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.

Keywords: Supply chain network; Multi-objective model; Mixed-integer linear programming; Robust optimization; COVID-19 outbreak (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10668-022-02604-z

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