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Presenting an agile supply chain mathematical model for COVID-19 (Corona) drugs using metaheuristic algorithms (case study: pharmaceutical industry)

This article focuses on the strategic issue of an agile supply chain. Different goals are considered in supply chain design. Today, the concept of sustainability in supply chains plays an important role in goal setting. In general, sustainability leads to less economic, social, and environmental ris...

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Autor principal: Shayannia, Seyed Ahmad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9398903/
https://www.ncbi.nlm.nih.gov/pubmed/35999421
http://dx.doi.org/10.1007/s11356-022-22608-6
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author Shayannia, Seyed Ahmad
author_facet Shayannia, Seyed Ahmad
author_sort Shayannia, Seyed Ahmad
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description This article focuses on the strategic issue of an agile supply chain. Different goals are considered in supply chain design. Today, the concept of sustainability in supply chains plays an important role in goal setting. In general, sustainability leads to less economic, social, and environmental risks, and attention to this type of sustainability covers many criteria in the literature. Therefore, in this study, optimization of the stability of a supply chain network has been considered. In addition, a lesser-known aspect of sustainability, the political aspect, has been added to the previous aspects. This paper assumes four levels, namely supplier, wholesaler, retailer, and customer. An optimal network structure is designed to consider economic, social, and environmental sustainability and the new measure of political sustainability. The design of this supply chain is done by defining a mathematical model that has several objective functions, including economic, political, and environmental goals. These objective functions select the relationships and links between the levels in a supply chain network. For this purpose, a directional graph corresponding to a supply chain is designed. Then, with the help of an ideal multi-objective planning problem, an optimal configuration is obtained, which is a subgraph of the main network graph. The target problem has been modeled for a holding company which is a supply chain for COVID-19 drugs. Then, problem is solved using Multi-objective Particle Swarm Optimization (MOPSO) metaheuristics algorithm and NSGAII multi-objective genetic algorithm. A comparison was carried out between these two methods, and the results indicated that MOPSO performed better. The value of the objective functions is calculated, and the best value for the considered functions is obtained. Also, the amount of drug supply has been obtained by two distributors. Also, the amount of medicine purchased by the customer from each pharmacy is determined.
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spelling pubmed-93989032022-08-24 Presenting an agile supply chain mathematical model for COVID-19 (Corona) drugs using metaheuristic algorithms (case study: pharmaceutical industry) Shayannia, Seyed Ahmad Environ Sci Pollut Res Int Research Article This article focuses on the strategic issue of an agile supply chain. Different goals are considered in supply chain design. Today, the concept of sustainability in supply chains plays an important role in goal setting. In general, sustainability leads to less economic, social, and environmental risks, and attention to this type of sustainability covers many criteria in the literature. Therefore, in this study, optimization of the stability of a supply chain network has been considered. In addition, a lesser-known aspect of sustainability, the political aspect, has been added to the previous aspects. This paper assumes four levels, namely supplier, wholesaler, retailer, and customer. An optimal network structure is designed to consider economic, social, and environmental sustainability and the new measure of political sustainability. The design of this supply chain is done by defining a mathematical model that has several objective functions, including economic, political, and environmental goals. These objective functions select the relationships and links between the levels in a supply chain network. For this purpose, a directional graph corresponding to a supply chain is designed. Then, with the help of an ideal multi-objective planning problem, an optimal configuration is obtained, which is a subgraph of the main network graph. The target problem has been modeled for a holding company which is a supply chain for COVID-19 drugs. Then, problem is solved using Multi-objective Particle Swarm Optimization (MOPSO) metaheuristics algorithm and NSGAII multi-objective genetic algorithm. A comparison was carried out between these two methods, and the results indicated that MOPSO performed better. The value of the objective functions is calculated, and the best value for the considered functions is obtained. Also, the amount of drug supply has been obtained by two distributors. Also, the amount of medicine purchased by the customer from each pharmacy is determined. Springer Berlin Heidelberg 2022-08-24 2023 /pmc/articles/PMC9398903/ /pubmed/35999421 http://dx.doi.org/10.1007/s11356-022-22608-6 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Research Article
Shayannia, Seyed Ahmad
Presenting an agile supply chain mathematical model for COVID-19 (Corona) drugs using metaheuristic algorithms (case study: pharmaceutical industry)
title Presenting an agile supply chain mathematical model for COVID-19 (Corona) drugs using metaheuristic algorithms (case study: pharmaceutical industry)
title_full Presenting an agile supply chain mathematical model for COVID-19 (Corona) drugs using metaheuristic algorithms (case study: pharmaceutical industry)
title_fullStr Presenting an agile supply chain mathematical model for COVID-19 (Corona) drugs using metaheuristic algorithms (case study: pharmaceutical industry)
title_full_unstemmed Presenting an agile supply chain mathematical model for COVID-19 (Corona) drugs using metaheuristic algorithms (case study: pharmaceutical industry)
title_short Presenting an agile supply chain mathematical model for COVID-19 (Corona) drugs using metaheuristic algorithms (case study: pharmaceutical industry)
title_sort presenting an agile supply chain mathematical model for covid-19 (corona) drugs using metaheuristic algorithms (case study: pharmaceutical industry)
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9398903/
https://www.ncbi.nlm.nih.gov/pubmed/35999421
http://dx.doi.org/10.1007/s11356-022-22608-6
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