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Modeling and Simulation Innovations for Advanced Logistics Systems Management
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Modeling and Simulation Innovations for Advanced Logistics Systems Management

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Social Science".

Deadline for manuscript submissions: 30 December 2025 | Viewed by 3417

Special Issue Editors

Dr. Yusheng Zhou

E-Mail Website
Guest Editor
Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hong Hum 999077, Hong Kong
Interests: maritime cluster analysis; investment decision-making and maritime behavioral analytics
Dr. Kum Fai Yuen

E-Mail Website
Guest Editor
School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639789, Singapore
Interests: renewable energy and sustainability; industrial engineering and design; machine-person interoperability; supply chain management; system resilience
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Modern logistics systems have become complex, highly integrated networks requiring sophisticated management strategies to ensure seamless supply chain operations. Modeling and simulation techniques are vital for optimizing logistics systems, enabling better decision-making, efficiency, and resilience in an ever-evolving market. With the rapid advancement of digital twins, predictive analytics, and agent-based modeling technologies, logistics systems managers can now proactively address challenges like demand fluctuations, route optimization, and risk management.

This Special Issue will explore the latest advances in modeling and simulation for logistics systems management, emphasizing applications that enhance adaptability, sustainability, and strategic planning. We welcome contributions that examine innovative methodologies, case studies on real-world implementations, and research tackling the unique logistics modeling challenges. The goal is to provide theoretical insights and practical solutions that can help shape the future of logistics systems management.

Dr. Yusheng Zhou
Dr. Kum Fai Yuen
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

  • logistics systems modeling
  • supply chain simulation
  • decision support for logistics systems
  • predictive analytics in logistics
  • risk management in logistics

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (5 papers)

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Research

19 pages, 2251 KB  
Article
An Optimization Model of Coupled Medical Material Dispatching Inside and Outside Epidemic Areas Considering Comprehensive Satisfaction
by Jun Yang, Xiaofei Ye, Shuyi Pei, Xingchen Yan, Tao Wang, Jun Chen, Pengjun Zheng and Rongjun Cheng
Systems 2025, 13(8), 714; https://doi.org/10.3390/systems13080714 - 19 Aug 2025
Viewed by 324
Abstract
This study addresses the critical challenge of emergency material distribution during atypical public health crises, using the COVID-19 pandemic in Hubei Province as a representative case. An innovative internal–external coupled dispatching framework is proposed by integrating regional medical resource allocation with cross-regional supply [...] Read more.
This study addresses the critical challenge of emergency material distribution during atypical public health crises, using the COVID-19 pandemic in Hubei Province as a representative case. An innovative internal–external coupled dispatching framework is proposed by integrating regional medical resource allocation with cross-regional supply chain networks. Our methodology employs the SEIR epidemiological model to forecast infection rates and corresponding material demands, then incorporates bidirectional dispatching efficiency as a key determinant of demand urgency. Through systematic risk stratification of affected areas, we develop a dual-objective optimization model that simultaneously minimizes logistical time and cost, solved by the NSGA-II algorithm. The results demonstrate that the internal–external coupled emergency material dispatching approach significantly enhances demand satisfaction in affected regions and improves overall dispatching effectiveness. This study offers practical recommendations and valuable references for emergency material dispatching during public health crises. Full article
(This article belongs to the Special Issue Modeling and Simulation Innovations for Advanced Logistics Systems Management)
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23 pages, 1506 KB  
Article
Dynamic Risk Assessment Framework for Tanker Cargo Operations: Integrating Game-Theoretic Weighting and Grey Cloud Modelling with Port-Specific Empirical Validation
by Lihe Feng, Binyue Xu, Chaojun Ding, Hongxiang Feng and Tianshou Liu
Systems 2025, 13(8), 697; https://doi.org/10.3390/systems13080697 - 14 Aug 2025
Viewed by 320
Abstract
The complex interdependencies among numerous safety risk factors influencing oil tanker loading/unloading operations constitute a focal point in academic research. To enhance safety management in oil port operations, this study conducts a risk analysis of oil tanker berthing and cargo transfer safety. Initially, [...] Read more.
The complex interdependencies among numerous safety risk factors influencing oil tanker loading/unloading operations constitute a focal point in academic research. To enhance safety management in oil port operations, this study conducts a risk analysis of oil tanker berthing and cargo transfer safety. Initially, safety risk factors are identified based on the Wu-li Shi-li Ren-li (WSR) systems methodology. Subsequently, a hybrid weighting approach integrating the Fuzzy Analytic Hierarchy Process (FAHP), G2 method, and modified CRITIC technique is employed to calculate indicator weights. These weights are then synthesised into a combined weight (GVW) using cooperative game theory and variable weight theory. Further, by integrating grey theory with the cloud model (GCM), a risk assessment is performed using Tianjin Port as a case study. Results indicate that the higher-risk indicators for Tianjin Port include vessel traffic density, safety of berthing/unberthing operations, safety of cargo transfer operations, safety of pipeline transfer operations, psychological resilience, proficiency of pilots and captains, and emergency management capability. The overall comprehensive risk evaluation value for Tianjin Port is 0.403, corresponding to a “Moderate Risk” level. Comparative experiments demonstrate that the results generated by this model align with those obtained through Fuzzy Comprehensive Evaluation Methods. However, the proposed GVW-GCM framework provides a more objective and accurate reflection of safety risks during tanker operations. Based on the computational outcomes, targeted recommendations for risk mitigation are presented. The integrated weighting model—incorporating game theory and variable weight concepts—coupled with the grey cloud methodology, establishes an interpretable and reusable analytical framework for the safety assessment of oil port operations under diverse port conditions. This approach provides critical decision support for constructing comprehensive management systems governing oil tanker loading/unloading operations. Full article
(This article belongs to the Special Issue Modeling and Simulation Innovations for Advanced Logistics Systems Management)
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18 pages, 728 KB  
Article
Digital Twins and Cross-Border Logistics Systems Risk Management Capability: An Innovation Diffusion Perspective
by Shuyan Li, Pengwei Jin, Saier Su, Jinge Yao and Qiwei Pang
Systems 2025, 13(8), 658; https://doi.org/10.3390/systems13080658 - 4 Aug 2025
Viewed by 533
Abstract
This study ground in the Innovation Diffusion Theory (IDT), explores the value of digital twin technology in cross-border logistics risk management. Using structural equation modeling, it examines how five innovation characteristics of digital twins—relative advantage, compatibility, complexity, trialability, and observability—influence risk management capabilities, [...] Read more.
This study ground in the Innovation Diffusion Theory (IDT), explores the value of digital twin technology in cross-border logistics risk management. Using structural equation modeling, it examines how five innovation characteristics of digital twins—relative advantage, compatibility, complexity, trialability, and observability—influence risk management capabilities, specifically robustness and resilience, within cross-border logistics systems. The findings reveal that relative advantage, compatibility, trialability, and observability significantly enhance both robustness and resilience, while complexity does not show a significant negative impact. Furthermore, the study confirms that improvements in risk management capabilities contribute positively to competitive performance. This research not only enriches the theoretical understanding of digital twin applications in cross-border logistics but also offers valuable insights for practical implementation by enterprises. Full article
(This article belongs to the Special Issue Modeling and Simulation Innovations for Advanced Logistics Systems Management)
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25 pages, 3203 KB  
Article
Modeling the Growth Dynamics of Logistics Performance: Industrialization, Environmental Technology, and Economic Transformation in Manufacturing Economies
by Umar Hayyat, Li Qian, Maleeha Saeed and Wajid Nawaz
Systems 2025, 13(5), 375; https://doi.org/10.3390/systems13050375 - 13 May 2025
Cited by 1 | Viewed by 756
Abstract
Global manufacturing economies have faced logistics performance challenges in recent decades. This study investigates the influence of industrialization, environmental technology, trade openness, foreign direct investment, and economic growth on the logistics performance index in the top 20 manufacturing economies from 2007 to 2023. [...] Read more.
Global manufacturing economies have faced logistics performance challenges in recent decades. This study investigates the influence of industrialization, environmental technology, trade openness, foreign direct investment, and economic growth on the logistics performance index in the top 20 manufacturing economies from 2007 to 2023. This study used an advanced panel approach to obtain robust results, cross-section dependency, a unit root test and a panel cointegration test. The panel quantile regression (PQL) and panel quantile estimates based on income methods were employed to analyze long-run and short-run estimations. The empirical results show that industrialization accelerated across all the quantiles except at the 10th quantile, while environmental technology had a significantly positive impact on logistics performance across all quantiles (10th–90th). Moreover, our baseline model was further supported by the fact that we used Driscoll–Kraay and Prais–Winsten’s estimates and a panel causality test. Our findings reveal that in manufacturing countries, industrialization, environmental technology, and economic growth have a positive impact on logistics performance. This study proposes several recommendations to improve industrialization and environmental technology in manufacturing countries to promote logistics performance. At the same time, more resources should be allocated for industrialization as well as environmental technologies to promote logistics performance. Full article
(This article belongs to the Special Issue Modeling and Simulation Innovations for Advanced Logistics Systems Management)
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22 pages, 525 KB  
Article
Growth Mechanism in Transformation and Upgrading of Logistics Industry
by Fangzhou Li, Xiaojia Yang, Ruili Zhu, Tao Li and Jingyi Liu
Systems 2025, 13(3), 202; https://doi.org/10.3390/systems13030202 - 15 Mar 2025
Viewed by 895
Abstract
Despite the crucial contribution of the logistics industry to economic development, existing research has yet to comprehensively explore how the integration of basic and emerging business models fuels growth during the transformation and upgrading process. To address this research gap, this study utilizes [...] Read more.
Despite the crucial contribution of the logistics industry to economic development, existing research has yet to comprehensively explore how the integration of basic and emerging business models fuels growth during the transformation and upgrading process. To address this research gap, this study utilizes provincial panel data from 30 regions covering the period from 2008 to 2022. By employing an intermediary effect model and a moderation effect model, we aim to uncover the underlying mechanisms driving growth. The findings reveal that the logistics industry can be categorized into traditional and emerging logistics elements, with the integration of traditional elements forming the fundamental business model. This foundational model serves as the primary driver of the logistics industry’s growth, exerting both direct and indirect influences on its expansion. Moreover, the level of economic development positively moderates these direct and indirect effects. These insights underscore the importance of enhancing infrastructure development, fostering business innovation, and promoting region-specific differentiated growth strategies. Full article
(This article belongs to the Special Issue Modeling and Simulation Innovations for Advanced Logistics Systems Management)
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