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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...

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Detalles Bibliográficos
Autores principales: Qin, Jin, Ni, Ling-lin, Shi, Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Scientific World Journal 2012
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.
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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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