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Systems
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Modeling and Optimization of Transportation and Logistics System
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Modeling and Optimization of Transportation and Logistics System

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Engineering".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 784

Special Issue Editors

Dr. Neven Grubišić

E-Mail Website
Guest Editor
Faculty of Maritime Studies, University of Rijeka, 51 000 Rijeka, Croatia
Interests: transport modeling; traffic simulation; vehicle routing; transport logistics; container terminals optimization; maritime transport
Dr. Luka Novačko

E-Mail Website1 Website2
Guest Editor
Faculty of Transport and Traffic Sciences, University of Zagreb, HR-10000 Zagreb, Croatia
Interests: transportation sciences; road transport; transport modeling; transport planning; traffic simulation

Special Issue Information

Dear Colleagues,

The increasing complexity of transportation and logistics systems, coupled with the rapid evolution of digital technologies, calls for innovative approaches in designing solutions that can enhance mobility and freight transport using artificial intelligence environments.

The advent of Logistics 4.0, characterized by the integration of the Internet of Things, digital twins, big data analytics, cloud computing, automation, and robotics, has redefined mobility networks and supply chain operations. However, the transition towards intelligent, adaptive, and sustainable logistics requires advanced methodologies and interdisciplinary collaboration.

This Special Issue focuses on simulation-based optimization and agent-based modeling as key tools for tackling the challenges of modern transportation systems. These methods enable us to explore complex interactions, non-standard or emergency behaviors, dynamic demand patterns, and real-time decision-making processes in logistics and mobility networks.

We invite researchers, practitioners, and policymakers to submit their latest work on transport modeling, logistics optimization, and smart mobility solutions. This Special Issue aspires to advance both theoretical foundations and practical implementations, fostering discussions that will shape the next generation of efficient, sustainable, and intelligent transportation and logistics systems.

We look forward to receiving your submissions and engaging in a stimulating academic exchange.

Dr. Neven Grubišić
Dr. Luka Novačko
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Systems is an international peer-reviewed open access monthly 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 2400 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

  • transport modeling
  • simulation-based optimization
  • freight logistics
  • intelligent transport systems
  • smart mobility

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Published Papers (1 paper)

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28 pages, 5030 KiB  
Review
Spatio-Temporal Graphs in Transportation: Challenges, Optimization, and Prospects
by Aleksandr Rakhmangulov, Nikita Osintsev and Pavel Mishkurov
Systems 2025, 13(4), 263; https://doi.org/10.3390/systems13040263 - 8 Apr 2025
Viewed by 583
Abstract
Intelligent and information systems in transportation record and accumulate large volumes of raw data on dynamic transportation processes. However, these data are not fully utilized for forecasting, real-time planning, and transportation management. Spatio-temporal graphs allow describing simultaneously both the structure of transportation systems [...] Read more.
Intelligent and information systems in transportation record and accumulate large volumes of raw data on dynamic transportation processes. However, these data are not fully utilized for forecasting, real-time planning, and transportation management. Spatio-temporal graphs allow describing simultaneously both the structure of transportation systems of different modes of transportation and the dynamics of transportation flows. Optimization of such graphs makes it possible to justify management decisions in real time, as well as to forecast the parameters of traffic flows and transportation processes. The purpose of the study is to identify trends in the use of spatio-temporal graphs for solving various problems in transportation, as well as the most common methods of optimization of such graphs. The sample papers studied include 114 publications from the Scopus database over 25 years, from 1999 to 2024. First, a bibliometric analysis was conducted to establish the increase in the number of publications, journals, countries, institutions, subject areas, articles, authors, and keyword matches, to understand the amount of literature generated. Secondly, a literature review was conducted based on content analysis to predict future research directions in the field. We have found that the development of deep learning methods and approaches for designing graph neural networks based on spatio-temporal graphs is a promising direction. Such methods are mostly used to solve the tasks of real-time control of urban transportation systems. There are fewer publications in areas that require in-depth knowledge of transportation technology, such as air, sea, and rail transportation. This study contributes to the expansion of scientific knowledge about methods of spatio-temporal optimization of transport systems based on bibliometric analysis. Full article
(This article belongs to the Special Issue Modeling and Optimization of Transportation and Logistics System)
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