PMID- 37143923
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20230507
IS  - 0957-4174 (Print)
IS  - 0957-4174 (Electronic)
IS  - 0957-4174 (Linking)
VI  - 225
DP  - 2023 Sep 1
TI  - Robust optimization and strategic analysis for agri-food supply chain under 
      pandemic crisis: Case study from an emerging economy.
PG  - 120081
LID - 10.1016/j.eswa.2023.120081 [doi]
AB  - Pandemic crises like the coronavirus disease 2019 (COVID-19) have severely 
      influenced companies working in the Agri-food industry in different countries. 
      Some companies could overcome this crisis by their elite managers, while many 
      experienced massive financial losses due to a lack of the appropriate strategic 
      planning. On the other hand, governments sought to provide food security to the 
      people during the pandemic crisis, putting extreme pressure on companies 
      operating in this field. Therefore, the aim of this study is to develop a model 
      of the canned food supply chain under uncertain conditions in order to analyze it 
      strategically during the COVID-19 pandemic. The problem uncertainty is addressed 
      using robust optimization, and also the necessity of using a robust optimization 
      approach compared to the nominal approach to the problem is indicated. Finally, 
      to face the COVID-19 pandemic, after determining the strategies for the canned 
      food supply chain, by solving a multi-criteria decision-making (MCDM) problem, 
      the best strategy is specified considering the criteria of the company under 
      study and its equivalent values are presented ​​as optimal values of a 
      mathematical model of canned food supply chain network. The results demonstrated 
      that "expanding the export of canned food to neighboring countries with economic 
      justification" was the best strategy for the company under study during the 
      COVID-19 pandemic. According to the quantitative results, implementing this 
      strategy reduced by 8.03% supply chain costs and increased by 3.65% the human 
      resources employed. Finally, the utilization of available vehicle capacity was 
      96%, and the utilization of available production throughput was 75.8% when using 
      this strategy.
CI  - (c) 2023 Elsevier Ltd. All rights reserved.
FAU - Rahbari, Misagh
AU  - Rahbari M
AD  - Department of Industrial Engineering, Faculty of Engineering, Kharazmi 
      University, Tehran, Iran.
FAU - Arshadi Khamseh, Alireza
AU  - Arshadi Khamseh A
AD  - Department of Industrial Engineering, Faculty of Engineering, Kharazmi 
      University, Tehran, Iran.
FAU - Mohammadi, Mohammad
AU  - Mohammadi M
AD  - Department of Industrial Engineering, Faculty of Engineering, Kharazmi 
      University, Tehran, Iran.
LA  - eng
PT  - Journal Article
DEP - 20230412
PL  - United States
TA  - Expert Syst Appl
JT  - Expert systems with applications
JID - 9884333
PMC - PMC10111269
OTO - NOTNLM
OT  - Agri-food Supply Chain
OT  - COVID-19
OT  - Canned Food
OT  - Robust Optimization
OT  - Strategic Management
COIS- The authors declare that they have no known competing financial interests or 
      personal relationships that could have appeared to influence the work reported in 
      this paper.
EDAT- 2023/05/05 06:42
MHDA- 2023/05/05 06:43
PMCR- 2023/04/12
CRDT- 2023/05/05 03:54
PHST- 2022/04/06 00:00 [received]
PHST- 2023/03/22 00:00 [revised]
PHST- 2023/04/06 00:00 [accepted]
PHST- 2023/05/05 06:43 [medline]
PHST- 2023/05/05 06:42 [pubmed]
PHST- 2023/05/05 03:54 [entrez]
PHST- 2023/04/12 00:00 [pmc-release]
AID - S0957-4174(23)00583-3 [pii]
AID - 120081 [pii]
AID - 10.1016/j.eswa.2023.120081 [doi]
PST - ppublish
SO  - Expert Syst Appl. 2023 Sep 1;225:120081. doi: 10.1016/j.eswa.2023.120081. Epub 
      2023 Apr 12.