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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Cost reduction is among the main quoted reasons for logistics outsourcing, while transport capacities and operations are among the most outsourced logistics areas. However, according to transaction costs theory, there is often room for transport insourcing. Furthermore, nowadays many authors stress that mixed solutions can give better results than “make” or “buy” alternatives. “Make or buy” decision-making normative models, methods, and procedures in transport planning are not much explored. Instead, research is rather focused on carrier selection techniques, whereby it is supposed that outsourcing transport capacities is the most suitable solution. The purpose of this paper is to contribute to the body of literature on classical “makeor-buy” decision-making in transport fleet sizing in a non-logistics enterprise. It goes beyond the basic “make or buy” decisionmaking, and intermediate solutions (i.e., “make and buy”) are explored. Practical directions are given according to theoretical principles, and a case study is used to exemplify the main deductions. The research also has practical implications. Many enterprises in transition economies have faced the question of what to do with their in-house transport fleets. The obtained results are of interest to merchants and manufacturing enterprises that already have a private transport fleet and are considering how to rationalize it

The paper presents the evaluation of the Eco-driving program impact (classroom with on-road instructions) on truck drivers' operation parameters. A total of 8 professional truck drivers were tested in the real driving conditions. Evaluation of the training impact on the drivers' behavior was done in three periods: intervention period (P1), one month after training (P2) and four months after training (P3). Data was collected with the assistance of the Scania Fleet Management System TM. Fuel economy and CO2 emission, idling time and coasting were significantly improved in the periods P2 and P3 compared to period P1 while speeding significantly increased. Statistically, the use of the brake did not significantly change in the first and fourth month after the completed training in comparison to the intervention period. The drivers' adoption of the eco-driving tips showed that statistically significant differences in fuel consumption and brake usage were obtained. This study shows that the use of the eco-driving techniques has got a potential for significant short-term reduction of fuel consumption and CO2 emission in road transport; hence in the future the research studies will deal with the effects of training and potential downtrend in the long run (> 6 months). Also, future research projects should analyze the impact of the drivers' socioeconomic characteristics on the application of the eco-driving instructions.

According to the European Committee (EC) on Transport, the future road transport strategy lies in creating a strong road transport sector which is based on a well-functioning internal market, fair competition and workers’ rights, decarbonization, and use of digital technologies. Urban and suburban passenger transportation systems, according to the principles of the EC, have a key role in achieving the goal of sustainable development and sustainable transport in cities. The fare, ticketing, and payment modes have a significant impact on public urban transport systems, primarily in terms of collecting transport service fees, and represent the basic source of financing of such systems, in addition to subsidies and grants from city budgets. This paper presents the selection methodology of the optimal fare system for urban public transport, applicable for all cities with an organized public city passenger transport (PCPT) system. Based on the established criteria with respect to setting tariff limits and fare systems, passenger demand, and the enterprise organizing the transport, the tariff system was selected. The presented method is that of multi- criteria optimization of the tariff system with numerical results on the example of the City of Novi Sad.