Planning the City Logistics Terminal Location by Applying the Greenp-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.

A New Geospatial Model Integrating a Fuzzy Rule-Based System in a GIS Platform to Partition a Complex Urban System in Homogeneous Urban Contexts

“…Formally, let n 5-9 be the number of residents in the microzone with an age in the range of 5-9 years, let n 10-14 be the number of residents in the microzone with an age in the range of 10-14 years, and let n [15][16][17][18][19] be the number of residents in the microzone with an age in the range of 15-19 years.…”

“…The indicator I 11 is given by the formula: I 11 = I 11a × n 5-9 + I 11b × n 10-14 + I 11c × n 15-19 n 5-9 +n 10-14 +n [15][16][17][18][19] (2)…”

“…Our goal is to model the knowledge and approximate reasoning of domain experts in order to apply them to partition the urban system. Fuzzy logic plays a key role in approximate reasoning, and Fuzzy Logic Systems [18][19][20] are implemented to manage approximate knowledge in order to solve specific problems through the use of approximate reasoning. The Mamdani fuzzy rule-based model is the most well-known fuzzy logic system model; it has been successfully applied in many fields, such as automatic control [21], expert systems [22], mobile robots [23], and computer vision [24].…”

Concept of logistics prevention development in a defence system

“…Logistics prevention should be constantly adjusted to supported system requests; on the other hand, supported systems must be designed taking into account logistics prevention requests. Supported systems also need to adapt to the possibilities of logistics systems (Atanasković et al, 2009, pp.127-139), (Pamučar et al, 2016).…”

Intelligent Parking Space Control in a System with Reservations

“…FLS and ANFIS are widely used methods for solving various traffic engineering problems. Many authors gave the contribution in this field, and some of them can be found in the recently published papers [27,28]. For example, in paper [27] the authors describe the problem of choice of road route under conditions of uncertainty which the drivers face as they carry out their task of transportation.…”