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Combined Simulated Annealing Algorithm for the Discrete Facility Location Problem
The combined simulated annealing (CSA) algorithm was developed for the discrete facility location problem (DFLP) in the paper. The method is a two-layer algorithm, in which the external subalgorithm optimizes the decision of the facility location decision while the internal subalgorithm optimizes th...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Scientific World Journal
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3459244/ https://www.ncbi.nlm.nih.gov/pubmed/23049474 http://dx.doi.org/10.1100/2012/576392 |
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author | Qin, Jin Ni, Ling-lin Shi, Feng |
author_facet | Qin, Jin Ni, Ling-lin Shi, Feng |
author_sort | Qin, Jin |
collection | PubMed |
description | The combined simulated annealing (CSA) algorithm was developed for the discrete facility location problem (DFLP) in the paper. The method is a two-layer algorithm, in which the external subalgorithm optimizes the decision of the facility location decision while the internal subalgorithm optimizes the decision of the allocation of customer's demand under the determined location decision. The performance of the CSA is tested by 30 instances with different sizes. The computational results show that CSA works much better than the previous algorithm on DFLP and offers a new reasonable alternative solution method to it. |
format | Online Article Text |
id | pubmed-3459244 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | The Scientific World Journal |
record_format | MEDLINE/PubMed |
spelling | pubmed-34592442012-10-03 Combined Simulated Annealing Algorithm for the Discrete Facility Location Problem Qin, Jin Ni, Ling-lin Shi, Feng ScientificWorldJournal Research Article The combined simulated annealing (CSA) algorithm was developed for the discrete facility location problem (DFLP) in the paper. The method is a two-layer algorithm, in which the external subalgorithm optimizes the decision of the facility location decision while the internal subalgorithm optimizes the decision of the allocation of customer's demand under the determined location decision. The performance of the CSA is tested by 30 instances with different sizes. The computational results show that CSA works much better than the previous algorithm on DFLP and offers a new reasonable alternative solution method to it. The Scientific World Journal 2012-09-19 /pmc/articles/PMC3459244/ /pubmed/23049474 http://dx.doi.org/10.1100/2012/576392 Text en Copyright © 2012 Jin Qin et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Qin, Jin Ni, Ling-lin Shi, Feng Combined Simulated Annealing Algorithm for the Discrete Facility Location Problem |
title | Combined Simulated Annealing Algorithm for the Discrete Facility Location Problem |
title_full | Combined Simulated Annealing Algorithm for the Discrete Facility Location Problem |
title_fullStr | Combined Simulated Annealing Algorithm for the Discrete Facility Location Problem |
title_full_unstemmed | Combined Simulated Annealing Algorithm for the Discrete Facility Location Problem |
title_short | Combined Simulated Annealing Algorithm for the Discrete Facility Location Problem |
title_sort | combined simulated annealing algorithm for the discrete facility location problem |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3459244/ https://www.ncbi.nlm.nih.gov/pubmed/23049474 http://dx.doi.org/10.1100/2012/576392 |
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