Operational vehicle quality measures are an important element used to evaluate the performance of transport services. In practice, there are many methods involved in the operational evaluation of vehicles. They are characterized in this article. Artificial Intelligence methods, especially artificial neural networks, can also be successfully used for this purpose, and especially when deciding on quality assessment processes for machines, including motor vehicles. The use of methods to support decision-making based on facts is extremely important for the credibility and objectivity of the evaluation. These methods can also be used in relation to the use of vehicles in the assessment of transport services. The article presents the method of using artificial neural networks for the operational evaluation of vehicles used in freight transport services. The basis for the verification of the method was an experimental research carried out at a company making dairy products, cooperating with transport companies, supplying products for the production process. The results obtained from the operation of vehicles from the studied companies have confirmed, at the probability level of 99%, high efficiency of the proposed method in evaluating transport services using operational vehicle quality measures.

The problem of sustainable transport system development is currently very important and frequently analysed. It concerns promotion of such transport, which is efficient, cost effective and meets the expectations of the society. At the same time, such transport should minimize its negative impact on public health, environment, and economy or urban planning. This paper deals with selected aspects of developing sustainable transport systems and assessing them based on their negative impact on society (amount of pollution and noise emissions). A number of different scenarios for the sustainable transport system development were presented. In addition, a procedure for evaluating these scenarios was proposed (using appropriate evaluation criteria and indicators, including noise and pollutant emissions from road transport). The studies presented in this paper were carried out using the PTV Visum tool and transport models developed in it (e.g. EMITRANSYS or MTAW 2015).

The facility location problem is a popular issue in the literature. The current development of world economies and globalization of the market requires continuous improvement of methods and research in this field. The location of the object determines the time of transport, affects the operational costs of the supply chain, and determines the possible amount of inventory or minimum inventory levels. These are critical issues from the point of view of designing an effective logistics system. The degree of complexity of current decision-making problems requires the construction of mathematical models and support for the decision-maker by optimization and simulation methods. A comprehensive and systemic approach to the problem allows the effective planning of supply chains. The purpose of this article was to study the sensitivity of the warehouse location problem in the supply chain. The solution was obtained based on the methodology developed under the SIMMAG3D project. The article presents the characteristics of the issue of the location of warehouse objects, the mathematical formulation of the solved problem of location and the method of its solution based on the heuristic algorithm using the modification of the Busacker-Gowen method. Then, a supply chain simulation model was developed in the FLEXSIM environment and scenario studies were performed for various input data and model parameters. The analysis and assessment of the solution based on parameters such as utilization of the potential of warehouse objects object were presented. Random change in demand described by Erlang distribution and normal distribution was considered. The analysis showed how the selection of a statistical distribution to describe the input data can affect the shape of the logistics system. The article ends with a summary of considerations and a plan for further research in the use of the simulation environment to support the decision-making process of the location of storage facilities and the functioning of supply chains.

Transport is a sector that is said to be negatively affecting the environment. The continuous development of transport increases the negative impact on the environment and civilization. In the article authors present the parameters that were used to describe the size of harmful transport exhaust emissions, in particular by means of road transport and the factors affecting their size. The areas where the level of concentrations of air pollutants are exceeded in Poland were characterized and analysed. Also examples of the stream traffic distribution in the selected area of the transport network were presented.

This study addresses the critical gap in the literature regarding the energy efficiency of intermodal terminals in smart cities, mainly focusing on crane operations during train loading processes. Novelty’s contribution lies in developing a comprehensive simulation model in FlexSim, where quantitative analysis of crane energy consumption, factoring in container location in the storage yard, rehandling operations, and crane movement strategies were performed. Moreover, the analysis of hoist, trolley, and gantry movements was performed to evaluate their impact on overall container loading process energy efficiency. The findings reveal that the choice of train loading method significantly influences crane energy consumption, thereby affecting the operational costs, environmental footprint, and energy efficiency of the logistics hub in the form of an intermodal terminal. This research provides a methodology for assessing and enhancing the energy efficiency of intermodal terminals and highlights the broader implications for smart city sustainability goals, including reduced greenhouse gas emissions, lower operating costs, and improved transportation infrastructure. The outcomes of this research can possibly support smart city planners and logistics managers in making informed decisions to optimise intermodal terminal operations, contributing to urban areas’ sustainable development and economic resilience.