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Transportation Optimization with Fuzzy Trapezoidal Numbers Based on Possibility Theory
In this paper, a parametric method is introduced to solve fuzzy transportation problem. Considering that parameters of transportation problem have uncertainties, this paper develops a generalized fuzzy transportation problem with fuzzy supply, demand and cost. For simplicity, these parameters are as...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4138112/ https://www.ncbi.nlm.nih.gov/pubmed/25137239 http://dx.doi.org/10.1371/journal.pone.0105142 |
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author | He, Dayi Li, Ran Huang, Qi Lei, Ping |
author_facet | He, Dayi Li, Ran Huang, Qi Lei, Ping |
author_sort | He, Dayi |
collection | PubMed |
description | In this paper, a parametric method is introduced to solve fuzzy transportation problem. Considering that parameters of transportation problem have uncertainties, this paper develops a generalized fuzzy transportation problem with fuzzy supply, demand and cost. For simplicity, these parameters are assumed to be fuzzy trapezoidal numbers. Based on possibility theory and consistent with decision-makers' subjectiveness and practical requirements, the fuzzy transportation problem is transformed to a crisp linear transportation problem by defuzzifying fuzzy constraints and objectives with application of fractile and modality approach. Finally, a numerical example is provided to exemplify the application of fuzzy transportation programming and to verify the validity of the proposed methods. |
format | Online Article Text |
id | pubmed-4138112 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-41381122014-08-20 Transportation Optimization with Fuzzy Trapezoidal Numbers Based on Possibility Theory He, Dayi Li, Ran Huang, Qi Lei, Ping PLoS One Research Article In this paper, a parametric method is introduced to solve fuzzy transportation problem. Considering that parameters of transportation problem have uncertainties, this paper develops a generalized fuzzy transportation problem with fuzzy supply, demand and cost. For simplicity, these parameters are assumed to be fuzzy trapezoidal numbers. Based on possibility theory and consistent with decision-makers' subjectiveness and practical requirements, the fuzzy transportation problem is transformed to a crisp linear transportation problem by defuzzifying fuzzy constraints and objectives with application of fractile and modality approach. Finally, a numerical example is provided to exemplify the application of fuzzy transportation programming and to verify the validity of the proposed methods. Public Library of Science 2014-08-19 /pmc/articles/PMC4138112/ /pubmed/25137239 http://dx.doi.org/10.1371/journal.pone.0105142 Text en © 2014 He et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article He, Dayi Li, Ran Huang, Qi Lei, Ping Transportation Optimization with Fuzzy Trapezoidal Numbers Based on Possibility Theory |
title | Transportation Optimization with Fuzzy Trapezoidal Numbers Based on Possibility Theory |
title_full | Transportation Optimization with Fuzzy Trapezoidal Numbers Based on Possibility Theory |
title_fullStr | Transportation Optimization with Fuzzy Trapezoidal Numbers Based on Possibility Theory |
title_full_unstemmed | Transportation Optimization with Fuzzy Trapezoidal Numbers Based on Possibility Theory |
title_short | Transportation Optimization with Fuzzy Trapezoidal Numbers Based on Possibility Theory |
title_sort | transportation optimization with fuzzy trapezoidal numbers based on possibility theory |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4138112/ https://www.ncbi.nlm.nih.gov/pubmed/25137239 http://dx.doi.org/10.1371/journal.pone.0105142 |
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