Robust optimization and strategic analysis for agri-food supply chain under pandemic crisis: Case study from an emerging economy.

Agri-food Supply Chain COVID-19 Canned Food Robust Optimization Strategic Management

Journal

Expert systems with applications
ISSN: 0957-4174
Titre abrégé: Expert Syst Appl
Pays: United States
ID NLM: 9884333

Informations de publication

Date de publication:
01 Sep 2023
Historique:
received: 06 04 2022
revised: 22 03 2023
accepted: 06 04 2023
medline: 5 5 2023
pubmed: 5 5 2023
entrez: 5 5 2023
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 37143923
doi: 10.1016/j.eswa.2023.120081
pii: S0957-4174(23)00583-3
pmc: PMC10111269
doi:

Types de publication

Journal Article

Langues

eng

Pagination

120081

Informations de copyright

© 2023 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

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.

Références

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Auteurs

Misagh Rahbari (M)

Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran.

Alireza Arshadi Khamseh (A)

Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran.

Mohammad Mohammadi (M)

Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran.

Classifications MeSH