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Mathematics
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Modeling of Processes in Transport Systems
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Modeling of Processes in Transport Systems

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".

Deadline for manuscript submissions: 31 May 2026 | Viewed by 2948

Special Issue Editors

Prof. Dr. Momčilo Dobrodolac

E-Mail Website
Guest Editor
Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, 11000 Belgrade, Serbia
Interests: postal services; transportation science; decision-making; optimization algorithms; fuzzy logic
Special Issues, Collections and Topics in MDPI journals
Dr. Dragan Lazarević

E-Mail Website
Guest Editor
Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, 11000 Belgrade, Serbia
Interests: postal services; transportation science; decision-making; geometric modeling and visualization; new technologies
Dr. Aleksandar Trifunović

E-Mail Website
Guest Editor
Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, 11000 Belgrade, Serbia
Interests: geometric modeling and visualization; traffic safety; perception; new technologies

Special Issue Information

Dear Colleagues,

Mathematical modeling plays a crucial role in understanding, analyzing, and optimizing processes within transport systems. As the transport sector faces increasing demands for safety, efficiency, resilience, and sustainability, the application of advanced mathematical tools is becoming increasingly important. Transport systems are inherently complex and often operate under dynamic, uncertain, or multi-variable conditions, making them ideal candidates for rigorous modeling approaches.

This Special Issue aims to bring together high-quality contributions that demonstrate the development and application of mathematical models and simulations in the field of transport systems. Topics of interest include, but are not limited to, the following: mathematical and geometric modeling; traffic flow and safety analyses; transport network optimization; data-driven decision-making; and the use of soft computing techniques such as fuzzy logic, machine learning, neural networks, or hybrid algorithms. Both theoretical advancements and practical implementations are welcome, with an emphasis on interdisciplinary approaches that bridge mathematics and engineering practice. We invite researchers from academia, industry, and government institutions to submit their original research articles, review papers, or case studies addressing contemporary challenges through modeling in transport systems.

Prof. Dr. Momčilo Dobrodolac
Dr. Dragan Lazarević
Dr. Aleksandar Trifunović
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • mathematical modeling
  • transport systems
  • optimization
  • simulation
  • safety
  • sustainable transport
  • last-mile delivery
  • infrastructure
  • traffic analysis
  • geometric modeling
  • decision-making
  • fuzzy approach
  • machine learning
  • artificial intelligence

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Related Special Issue

Published Papers (2 papers)

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Research

23 pages, 2546 KB  
Article
Data-Driven Predictive Modeling of Passenger-Accepted Vehicle Occupancy in Transport Systems
by Katarina Trifunović, Tijana Ivanišević, Aleksandar Trifunović, Svetlana Čičević, Draženko Glavić, Gabriel Fedorko and Vieroslav Molnar
Mathematics 2026, 14(8), 1274; https://doi.org/10.3390/math14081274 (registering DOI) - 11 Apr 2026
Abstract
Mathematical modeling plays a key role in understanding and optimizing transport system operations under uncertain and dynamic conditions. This study proposes a data-driven predictive framework for estimating passenger-accepted vehicle occupancy, addressing a critical gap in transport system planning under public health-related constraints. Using [...] Read more.
Mathematical modeling plays a key role in understanding and optimizing transport system operations under uncertain and dynamic conditions. This study proposes a data-driven predictive framework for estimating passenger-accepted vehicle occupancy, addressing a critical gap in transport system planning under public health-related constraints. Using data from a structured survey conducted across seven Southeast European countries (N = 476), the study integrates statistical analysis and machine learning approaches to model acceptable occupancy levels across multiple transport modes, including passenger cars, taxis, tourist buses, and public buses. The problem is formulated as a predictive mapping between multidimensional input variables and occupancy acceptance levels, modeled using both probabilistic and nonlinear function approximation methods. The results highlight that age, gender, and area of residence are the most significant determinants of occupancy acceptance, while education level has limited predictive relevance. Furthermore, a multi-layer feedforward artificial neural network is developed to capture nonlinear relationships between variables, achieving strong predictive performance (minimum MSE = 0.0089). The main contribution of this research lies in linking behavioral data with predictive modeling to quantify acceptable occupancy thresholds and support realistic simulation of passenger responses in crisis conditions. The proposed modeling framework contributes to transport system planning, enabling data-driven capacity management, enhanced safety strategies, and improved resilience of passenger transport operations. Full article
(This article belongs to the Special Issue Modeling of Processes in Transport Systems)
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32 pages, 1990 KB  
Article
Assessment of Efficiency of Last-Mile Delivery Zones: A Novel IRN OWCM–IRN AROMAN Model
by Bojan Jovanović, Željko Stević, Jelena Mitrović Simić, Aleksandra Stupar and Miloš Kopić
Mathematics 2025, 13(17), 2845; https://doi.org/10.3390/math13172845 - 3 Sep 2025
Viewed by 1465
Abstract
The importance of managing goods delivery in urban areas has reached its peak in recent years, driven by the constant and rapid growth of online commerce. Under such conditions, where smaller quantities of goods are ordered, yet the number of shipments continues to [...] Read more.
The importance of managing goods delivery in urban areas has reached its peak in recent years, driven by the constant and rapid growth of online commerce. Under such conditions, where smaller quantities of goods are ordered, yet the number of shipments continues to rise, the question of last-mile delivery (LMD) efficiency becomes increasingly relevant. This paper addresses the issue of last-mile delivery zone efficiency through the application of a new methodological approach. First, the concept of measuring last-mile delivery productivity is defined using a specific example from an urban environment. Next, Key Performance Indicators (KPIs) are established to enable a proper assessment of urban zone efficiency in line with the LMD concept. The main contribution of this study is the development of the IRN OWCM (Interval Rough Number Opinion Weight Criteria Method), which is used to calculate the weights of the criteria. To assess suitable delivery zones in terms of efficiency based on the defined KPIs, the previously developed IRN OWCM method is integrated with IRN AROMAN (Alternative Ranking Order Method Accounting for Two-Step Normalization). The results identify delivery zones that are suitable in terms of meeting standardized user needs. The developed model demonstrated stability through additional verification tests and can be adequately applied in cases when it is needed to minimize subjectivity and uncertainties. Full article
(This article belongs to the Special Issue Modeling of Processes in Transport Systems)
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