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Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network

The paper herein presents green p-median problem (GMP) which uses the adaptive type-2 neural network for the processing of environmental and sociological parameters including costs of logistics operators and demonstrates the influence of these parameters on planning the location for the city logisti...

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Autores principales: Pamučar, Dragan, Vasin, Ljubislav, Atanasković, Predrag, Miličić, Milica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4853964/
https://www.ncbi.nlm.nih.gov/pubmed/27195005
http://dx.doi.org/10.1155/2016/6972818
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author Pamučar, Dragan
Vasin, Ljubislav
Atanasković, Predrag
Miličić, Milica
author_facet Pamučar, Dragan
Vasin, Ljubislav
Atanasković, Predrag
Miličić, Milica
author_sort Pamučar, Dragan
collection PubMed
description The paper herein presents green p-median problem (GMP) which uses the adaptive type-2 neural network for the processing of environmental and sociological parameters including costs of logistics operators and demonstrates the influence of these parameters on planning the location for the city logistics terminal (CLT) within the discrete network. CLT shows direct effects on increment of traffic volume especially in urban areas, which further results in negative environmental effects such as air pollution and noise as well as increased number of urban populations suffering from bronchitis, asthma, and similar respiratory infections. By applying the green p-median model (GMM), negative effects on environment and health in urban areas caused by delivery vehicles may be reduced to minimum. This model creates real possibilities for making the proper investment decisions so as profitable investments may be realized in the field of transport infrastructure. The paper herein also includes testing of GMM in real conditions on four CLT locations in Belgrade City zone.
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spelling pubmed-48539642016-05-18 Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network Pamučar, Dragan Vasin, Ljubislav Atanasković, Predrag Miličić, Milica Comput Intell Neurosci Research Article The paper herein presents green p-median problem (GMP) which uses the adaptive type-2 neural network for the processing of environmental and sociological parameters including costs of logistics operators and demonstrates the influence of these parameters on planning the location for the city logistics terminal (CLT) within the discrete network. CLT shows direct effects on increment of traffic volume especially in urban areas, which further results in negative environmental effects such as air pollution and noise as well as increased number of urban populations suffering from bronchitis, asthma, and similar respiratory infections. By applying the green p-median model (GMM), negative effects on environment and health in urban areas caused by delivery vehicles may be reduced to minimum. This model creates real possibilities for making the proper investment decisions so as profitable investments may be realized in the field of transport infrastructure. The paper herein also includes testing of GMM in real conditions on four CLT locations in Belgrade City zone. Hindawi Publishing Corporation 2016 2016-04-19 /pmc/articles/PMC4853964/ /pubmed/27195005 http://dx.doi.org/10.1155/2016/6972818 Text en Copyright © 2016 Dragan Pamučar et al. https://creativecommons.org/licenses/by/4.0/ 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
Pamučar, Dragan
Vasin, Ljubislav
Atanasković, Predrag
Miličić, Milica
Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network
title Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network
title_full Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network
title_fullStr Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network
title_full_unstemmed Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network
title_short Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network
title_sort planning the city logistics terminal location by applying the green p-median model and type-2 neurofuzzy network
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4853964/
https://www.ncbi.nlm.nih.gov/pubmed/27195005
http://dx.doi.org/10.1155/2016/6972818
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