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Design and optimization of a sustainable and resilient mask supply chain during the COVID-19 pandemic: a multi-objective approach
被引:14
作者:
Alizadeh-Meghrazi, Milad
[1
,4
]
Tosarkani, Babak Mohamadpour
[2
]
Amin, Saman Hassanzadeh
[3
]
Popovic, Milos R.
[1
]
Ahi, Payman
[3
]
机构:
[1] Univ Toronto, Inst Biomed Engn, Toronto, ON, Canada
[2] Univ British Columbia, Sch Engn, Okanagan Campus, Kelowna, BC, Canada
[3] Toronto Metropolitan Univ, Dept Mech & Ind Engn, Toronto, ON, Canada
[4] Myant Inc, Etobicoke, ON, Canada
基金:
英国科研创新办公室;
关键词:
Supply chain network;
Multi-objective model;
Mixed-integer linear programming;
Robust optimization;
COVID-19;
outbreak;
QUALITY FUNCTION DEPLOYMENT;
REVERSE LOGISTICS NETWORK;
FACILITY LOCATION MODEL;
ROBUST OPTIMIZATION;
PROGRAMMING APPROACH;
GENETIC ALGORITHM;
DUAL-CHANNEL;
FUZZY QFD;
LOOP;
UNCERTAINTY;
D O I:
10.1007/s10668-022-02604-z
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
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.
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页数:46
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