Disaster relief supply chain design for personal protection equipment during the COVID-19 pandemic

被引:82
作者
Mosallanezhad, Behzad [1 ]
Chouhan, Vivek Kumar [2 ]
Paydar, Mohammad Mahdi [3 ]
Hajiaghaei-Keshteli, Mostafa [1 ]
机构
[1] Tecnol Monterrey, Escuela Ingn & Ciencias, Puebla, Mexico
[2] Indian Inst Informat Technol Design & Mfg, Dept Mech Engn, Chennai, Tamil Nadu, India
[3] Babol Noshirvani Univ Technol, Dept Ind Engn, Babol, Iran
关键词
Supply chain design; Personal protection equipment; COVID-19; Pandemic; Disaster relief supply chain; PROGRAMMING-MODEL; OPTIMIZATION; EVOLUTIONARY; ALGORITHM; SELECTION;
D O I
10.1016/j.asoc.2021.107809
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The global epidemic caused by novel coronavirus continues to be a crisis in the world and a matter of concern. The way the epidemic has wreaked havoc on the international level has become difficult for the healthcare systems to supply adequately personal protection equipment for medical personnel all over the globe. In this paper, considering the COVID-19 outbreak, a multi-objective, multi-product, and multi-period model for the personal protection equipment demands satisfaction aiming to optimize total cost and shortage, simultaneously, is developed. The model is embedded with instances and validated by both modern and classic multi-objective metaheuristic algorithms. Moreover, the Taguchi method is exploited to set the metaheuristic into their best performances by finding their parameters' optimum level. Furthermore, fifteen test examples are designed to prove the established PPE supply chain model and tuned algorithms' applicability. Among the test examples, one is related to a real case study in Iran. Finally, metaheuristics are evaluated by a series of related metrics through different statistical analyses. It can be concluded from the obtained results that solution methods are practical and valuable to achieve the efficient shortage level and cost. (C) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页数:20
相关论文
共 79 条
[1]  
Abbasi B., 2020, MODELING VACCINE ALL
[2]   A set of calibrated metaheuristics to address a closed-loop supply chain network design problem under uncertainty [J].
Abdi, Anita ;
Abdi, Andisheh ;
Fathollahi-Fard, Amir Mohammad ;
Hajiaghaei-Keshteli, Mostafa .
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS, 2021, 8 (01) :23-40
[3]   A novel option contract integrated with supplier selection and inventory prepositioning for humanitarian relief supply chains [J].
Aghajani, Mojtaba ;
Torabi, S. Ali ;
Heydari, Jafar .
SOCIO-ECONOMIC PLANNING SCIENCES, 2020, 71
[4]   Designing an integrated pharmaceutical relief chain network under demand uncertainty [J].
Akbarpour, Mina ;
Torabi, S. Ali ;
Ghavamifar, Ali .
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2020, 136 (136)
[5]   Vehicle routing and resource distribution in postdisaster humanitarian relief operations [J].
Al Theeb, Nader ;
Murray, Chase .
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, 2017, 24 (06) :1253-1284
[6]  
Barman Abhijit, 2021, Curr Res Behav Sci, V2, P100017, DOI 10.1016/j.crbeha.2021.100017
[7]   Stopping Covid-19: A pandemic-management service value chain approach [J].
Baveja, Alok ;
Kapoor, Ajai ;
Melamed, Benjamin .
ANNALS OF OPERATIONS RESEARCH, 2020, 289 (02) :173-184
[8]   Hybrid flowshop scheduling with machine and resource-dependent processing times [J].
Behnamian, J. ;
Ghomi, S. M. T. Fatemi .
APPLIED MATHEMATICAL MODELLING, 2011, 35 (03) :1107-1123
[9]   Manufacturing and service supply chain resilience to the COVID-19 outbreak: Lessons learned from the automobile and airline industries [J].
Belhadi, Amine ;
Kamble, Sachin ;
Jabbour, Charbel Jose Chiappetta ;
Gunasekaran, Angappa ;
Ndubisi, Nelson Oly ;
Venkatesh, Mani .
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2021, 163
[10]   A novel multi-objective programming model of relief distribution for sustainable disaster supply chain in large-scale natural disasters [J].
Cao, Cejun ;
Li, Congdong ;
Yang, Qin ;
Liu, Yang ;
Qu, Ting .
JOURNAL OF CLEANER PRODUCTION, 2018, 174 :1422-1435