title: Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network.
abstract: 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.
authors.affiliation: Department of Logistics, University of Defence in Belgrade, Pavla Jurisica Sturma 33, 11000 Belgrade, Serbia.
authors.forename: Dragan
authors.initials: D
authors.lastname: Pamučar
authors.affiliation: Department of Logistics, University of Defence in Belgrade, Pavla Jurisica Sturma 33, 11000 Belgrade, Serbia.
authors.forename: Ljubislav
authors.initials: L
authors.lastname: Vasin
authors.affiliation: Faculty of Technical Science, University of Novi Sad, Dositeja Obradovića 6, 21 000 Novi Sad, Serbia.
authors.forename: Predrag
authors.initials: P
authors.lastname: Atanasković
authors.affiliation: Faculty of Technical Science, University of Novi Sad, Dositeja Obradovića 6, 21 000 Novi Sad, Serbia.
authors.forename: Milica
authors.initials: M
authors.lastname: Miličić
mesh_terms: D000397:Air Pollution; D002947:Cities; D002958:City Planning / Q000191:economics; D004784:Environmental Monitoring / Q000379:methods; D006801:Humans; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D009934:Organization and Administration; D001335:Vehicle Emissions
chemical_list: D001335:Vehicle Emissions