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Location management for the supply of PD fluid via large neighborhood search based virus optimization algorithm
The facility location problem is extended by a new two-stage zero-one programming system (2S-ZOPS). It is a type of design optimization issue that exists in logistics implementations such as supply chain planning in healthcare or agriculture. Along with concerns regarding PD delivery time manner for...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758138/ https://www.ncbi.nlm.nih.gov/pubmed/36526703 http://dx.doi.org/10.1038/s41598-022-26385-7 |
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author | Atthirawong, Walailak Luangpaiboon, Pongchanun |
author_facet | Atthirawong, Walailak Luangpaiboon, Pongchanun |
author_sort | Atthirawong, Walailak |
collection | PubMed |
description | The facility location problem is extended by a new two-stage zero-one programming system (2S-ZOPS). It is a type of design optimization issue that exists in logistics implementations such as supply chain planning in healthcare or agriculture. Along with concerns regarding PD delivery time manner for connecting logistics centers and customers, recent studies have considered the zero-one location design model. This research discussed a route selection model for the 2S-ZOPS that did not exist in the published studies by taking into account the level of risk associated with physical appearance. The mathematical models were developed in response to a PD supply chain design that occurred in Thailand’s National Health Insurance Program. By combining the virus optimization algorithm (VOA) with a large neighborhood search (LNS), we created a hybrid metaheuristic method for solving the 2S-ZOPS. Experiments with real-world data demonstrated that the hybrid algorithm was efficient in terms of time consumption and solution quality, saving approximately 6% on total costs. The presented practice benefits not only the healthcare industry but also various other businesses. |
format | Online Article Text |
id | pubmed-9758138 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-97581382022-12-18 Location management for the supply of PD fluid via large neighborhood search based virus optimization algorithm Atthirawong, Walailak Luangpaiboon, Pongchanun Sci Rep Article The facility location problem is extended by a new two-stage zero-one programming system (2S-ZOPS). It is a type of design optimization issue that exists in logistics implementations such as supply chain planning in healthcare or agriculture. Along with concerns regarding PD delivery time manner for connecting logistics centers and customers, recent studies have considered the zero-one location design model. This research discussed a route selection model for the 2S-ZOPS that did not exist in the published studies by taking into account the level of risk associated with physical appearance. The mathematical models were developed in response to a PD supply chain design that occurred in Thailand’s National Health Insurance Program. By combining the virus optimization algorithm (VOA) with a large neighborhood search (LNS), we created a hybrid metaheuristic method for solving the 2S-ZOPS. Experiments with real-world data demonstrated that the hybrid algorithm was efficient in terms of time consumption and solution quality, saving approximately 6% on total costs. The presented practice benefits not only the healthcare industry but also various other businesses. Nature Publishing Group UK 2022-12-16 /pmc/articles/PMC9758138/ /pubmed/36526703 http://dx.doi.org/10.1038/s41598-022-26385-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Atthirawong, Walailak Luangpaiboon, Pongchanun Location management for the supply of PD fluid via large neighborhood search based virus optimization algorithm |
title | Location management for the supply of PD fluid via large neighborhood search based virus optimization algorithm |
title_full | Location management for the supply of PD fluid via large neighborhood search based virus optimization algorithm |
title_fullStr | Location management for the supply of PD fluid via large neighborhood search based virus optimization algorithm |
title_full_unstemmed | Location management for the supply of PD fluid via large neighborhood search based virus optimization algorithm |
title_short | Location management for the supply of PD fluid via large neighborhood search based virus optimization algorithm |
title_sort | location management for the supply of pd fluid via large neighborhood search based virus optimization algorithm |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758138/ https://www.ncbi.nlm.nih.gov/pubmed/36526703 http://dx.doi.org/10.1038/s41598-022-26385-7 |
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