Zdenka Bulková

Background: Warehouse location and freight vehicle selection are two strategic decisions that significantly influence the efficiency of industrial distribution systems. Although these decisions are usually addressed separately, they can be organized as consecutive stages within a common strategic planning process. This study proposes a sequential decision-support framework combining the Centre of Gravity (CoG) Method and the Forced Decision Matrix Method (FDMM). Methods: The framework comprises five sequential stages: customer demand analysis, warehouse location optimization, location validation, freight vehicle evaluation, and strategic decision support. It was validated using real operational data from a manufacturing enterprise in the Czech Republic. Warehouse location was determined from the aggregated annual transport demand of seven major customer locations (518,911 t), while twelve freight vehicle alternatives were evaluated using four technical and operational criteria. Results: The CoG analysis identified a demand-weighted candidate warehouse location at coordinates T (13.2, 3.5), corresponding to the vicinity of Nový Jičín. The FDMM identified the Scania R480 (D11) as the most suitable freight vehicle. Conclusions: The proposed framework provides a transparent and computationally efficient approach to strategic distribution planning by sequentially linking warehouse location analysis and freight vehicle selection within a single decision-support process.

This paper evaluates the efficiency of modernization of the regional railway line Prievidza–Jelšovce in Slovakia using cost–benefit analysis (CBA), reflecting increased investment costs and the potential electrification of the line. The assessment is based on a detailed analysis of transport demand and infrastructure conditions, where daily railway passenger volumes range between 2300 and 3700 passengers, while individual car transport exceeds 10,000 passengers per day in most sections. Two alternative modernization variants were evaluated. The results show that the project generates socio-economic benefits, particularly through travel time savings amounting to approximately €42.3 million and reductions in operating costs and externalities. Significant environmental benefits were identified, especially in the case of the more advanced variant, with reductions in air pollution reaching €56.3 million and greenhouse gas emissions reaching €42.2 million. Despite these benefits, the economic evaluation indicates negative net economic outcomes for both variants. The total economic investment costs (excluding VAT and adjusted for economic appraisal) reach €543.4 million for the EIA variant and €511.9 million for the proposed variant, resulting in net economic values of −€186.2 million and −€70.8 million, respectively. The results therefore suggest that neither variant achieves full economic efficiency under the given assumptions, although the proposed variant performs significantly better. The findings highlight the strong sensitivity of project efficiency to investment costs and the scope of modernization. The study confirms the necessity of regularly updating CBA analyses in transport projects, as changes in input parameters can substantially influence investment decision-making.

Public transport plays a key role in the mobility of the population and in the efficient functioning of both urban and suburban areas. Continuous technological advancement and the changing needs of passengers create new challenges and opportunities in the development of digital solutions for public transport. Mobile applications have become an integral part of travel, enabling users′ easier access to transport information, route planning, and ticket purchase. The aim of this article is to propose a methodology that systematically analyses existing digital solutions, identifies their shortcomings, and suggests new functionalities that will enhance the comfort and efficiency of public transport. The process includes a comprehensive approach ranging from the analysis of passenger behaviour and evaluation of existing applications to the proposal of innovative solutions, followed by their development, testing, and implementation. This systematic approach ensures that new technological solutions will be optimized for a wide range of users – from daily commuters to tourists and individuals with specific needs. The proposed solution is necessary in the context of future implementation of EU directives, and its results can contribute to increasing the competitiveness of public transport and its efficient use. The article provides a comprehensive methodology that serves as a key tool for innovation in public transport applications. This methodology contributes to improving the user experience, increasing the efficiency of transport services, and supporting the overall development of public transport.

Transportation systems are particularly vulnerable to disruptions such as pandemics, which create significant challenges for maintaining efficiency, safety, and service quality. This study focuses on rail passenger transport in the Slovak Republic and develops a simulation framework to evaluate system performance under crisis conditions. Weekly data from the national rail operator for the period 2019–2021 were combined with information on governmental restrictions, standardized into a five-level framework. A nonlinear autoregressive model with exogenous inputs (NARX), implemented and validated in MATLAB R2021b (MathWorks, Natick, MA, USA), was applied to simulate the impact of restrictive measures on passenger demand. The results revealed a strong relationship between the severity of measures and ridership levels, with the most significant effects observed in education, workplace access, movement limitations, and retail. For instance, during complete school closures, passenger volumes declined by up to 75% relative to the pre-pandemic baseline. Based on the simulation outcomes, recommendations were formulated for adapting railway operations, including dynamic adjustments of transport capacity (10–40%) according to restriction levels. The proposed modelling and simulation approach offers transport authorities a cost-effective tool for scenario testing, disruption management, and the design of resilient passenger rail systems capable of adapting to crises and uncertainties.

This paper introduces a novel multi-criteria evaluation system for railway sidings, designed to support sustainable freight transport and strategic infrastructure planning. The methodology is original because it integrates six criteria—technical, economic, operational, environmental, legal, and socio-economic—into a transparent scoring model based on the Analytic Hierarchy Process (AHP). This structured approach reduces subjectivity, ensures replicability, and enables the evidence-based prioritization of infrastructure investments. Policy relevance is emphasized by aligning the model with EU decarbonization targets and national railway development strategies, providing actionable guidance for decision-makers. The framework was applied to the SCP Mondi siding as a case study, achieving an Overall Quality Index (OQI) score of 4.175, categorizing it as a high-performing siding. Sensitivity analysis of weighting factors confirmed the model’s robustness and adaptability across different contexts. These results highlight the framework’s practical value in optimizing resource allocation, revitalizing underused infrastructure, and accelerating the modal shift to rail.

Efficient planning of train crew rosters is a key factor in ensuring operational reliability and promoting long-term sustainability in railway transport, both economically and socially. This article presents a systematic approach to developing a crew rostering model in passenger rail transport, with a focus on the operational setting of the train crew depot in Česká Třebová, a city in the Czech Republic. The seven-step methodology includes identifying available train shifts, defining scheduling constraints, creating roster variants, and calculating personnel and time requirements for each option. The proposed roster reduced staffing needs by two employees, increased the average shift duration to 9 h and 42 min, and decreased non-productive time by 384 h annually. These improvements enhance sustainability by optimizing human resource use, lowering unnecessary energy consumption, and improving employees’ work–life balance. The model also provides a quantitative assessment of operational feasibility and economic efficiency. Compared to existing rosters, the proposed model offers clear advantages and remains applicable even in settings with limited technological support. The findings show that a well-designed rostering system can contribute not only to cost savings and personnel stabilization, but also to broader objectives in sustainable public transport, supporting resilient and resource-efficient rail operations.

Urban public transport represents a fundamental pillar of a sustainable transport system and a key subsystem within the broader mobility framework in urban environments. This paper focuses on the analysis and optimization of the public transport system in the city of Prievidza and the nearby town of Bojnice in Slovakia, which currently face challenges such as low system attractiveness, operational inefficiency, and weak integration with regional railway transport. This study presents the results of a comprehensive analysis of existing public transport services in Prievidza and Bojnice, including an assessment of passenger flows, line network structure, transfer connections, and operational parameters. Based on the identified deficiencies, a new urban public transport network system is proposed, emphasizing direct links to the railway network. This methodology is developed in the context of an integrated timed-transfer timetable, with defined system time slots at the main transfer hub and a newly designed line network with standardized paths and regular intervals. The proposed system ensures significantly improved connectivity between urban transport and rail services, reduces deadhead kilometres, lowers the number of required vehicles, and leads to a reduction in operational costs by up to 20%. The resulting model serves as a transferable example of efficient service planning in medium-sized cities, with a focus on functional integration, operational efficiency, and sustainable urban development.

Modern cities and regions are increasingly challenged to effectively plan and develop transport systems that are not only functionally integrated but also long-term sustainable. Digital technologies offer new opportunities for collecting, processing, and evaluating data that can significantly enhance decision-making processes in the field of transport. This paper presents a concept of a digital decision-making framework that combines data-driven analytical tools, participatory platforms for stakeholder engagement, and multi-level evaluation based on sustainability criteria. The proposed framework is modular and is applied at the level of strategic planning of transport investments. The result is a more transparent, flexible, and evidence-based decision-making process that supports the balanced development of various modes of mobility.

The current technical condition of facilities designated for the technical–hygienic maintenance of railway rolling stock is unsatisfactory, as they are neither technologically nor technically equipped to meet the required quality standards. Maintenance is often carried out in open spaces or directly on the tracks of major railway junctions, which prevents year-round execution of these services and causes operational limitations. This article analyses and proposes solutions for the technical–hygienic maintenance center (THU) of railway rolling stock at the Nové Zámky railway station in Slovakia, focusing on improving the efficiency and quality of the provided services. The analysis includes an assessment of technological procedures, identification of operational deficiencies, and a comparison of current maintenance standards with the requirements for contemporary railway systems, such as automated diagnostic platforms, predictive maintenance modules, and modular cleaning infrastructure. The optimization of THU services considers the average time norms for selected technological procedures and the characteristics of train sets passing through the center. The proposed solution involves a more efficient scheduling of operations in line with the valid railway traffic timetable and train set circulation, utilizing a graphical planning method for modelling and optimizing the facility’s service processes. The implementation of optimization measures can lead to increased capacity and efficiency of maintenance, reduced time required for individual procedures, and lower operational costs. The study’s results provide practical recommendations for improving the quality of technical–hygienic maintenance at railway junction stations, contributing to greater railway transport reliability and an overall improvement in passenger comfort. Additionally, the findings offer a transferable framework that may inform the planning and modernization of maintenance facilities at other regional railway stations facing similar infrastructural and operational challenges.