Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
2.8
2.3
Journals
Systems
Special Issues
Application of System Engineering and Complex Theory in Transportation
share announcement

Application of System Engineering and Complex Theory in Transportation

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

Deadline for manuscript submissions: 30 November 2024 | Viewed by 4256

Special Issue Editors

Dr. Shuqi Xue

E-Mail Website
Guest Editor
School of Modern Posts, Xi'an University of Posts and Telecommunications, Xi’an 710121, China
Interests: transportation system optimization; traffic flow theory; pedestrian safety; passenger crowd dynamics and evacuation management
Special Issues, Collections and Topics in MDPI journals
Dr. Yun Wang

E-Mail Website
Guest Editor
School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Interests: public transport planning and management; transportation modeling and optimization; transportation emergency management
Dr. Xiaomeng Shi

E-Mail Website
Guest Editor
Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, 2 Dongnandaxue Rd, Nanjing 211189, China
Interests: active mode traffic; active traffic safety; human factors; intelligent transportation system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

System engineering, with its comprehensive approach to managing complex systems, plays a crucial role in addressing the inherent complexities of modern transportation systems. Complex theory, on the other hand, provides a framework for understanding the unpredictable and dynamic nature of transportation systems, enabling us to delve into the interactions among various elements within transportation system. This Special Issue focuses on exploring the latest research developments in the application of system engineering and complexity theory in the field of transportation, aiming to determine the potential of these disciplines in enhancing the efficiency, sustainability, and adaptability of transportation systems. The contents of this Special Issue will concentrate on new methods and approaches in system engineering for designing, analyzing, and implementing transportation solutions. We will also explore the role of complex theory in helping to understand and model nonlinear behaviors within transportation systems, aiming for more accurate predictions and management strategies. Additionally, this Special Issue pays special attention to potential research areas such as the integration of autonomous vehicles into existing transportation ecosystems, the application of intelligent technologies for dynamic traffic control, and the development of resilient infrastructure capable of adapting to changing demands and environmental conditions. Through these topics, we hope to provide a comprehensive overview of the current trends, challenges, and future directions in the application of system engineering and complexity theory in transportation. We eagerly invite researchers and practitioners who are pushing the boundaries in these fields to share their insights and discoveries. Your contributions will undoubtedly help shape the future of transportation systems, making them more intelligent, adaptable, and in-tune with rapidly evolving global needs.

Both original research and review works are welcome for submission. Research topics of interest include, but are not limited to, the following:

  • Smart city transportation systems;
  • Passenger behavioral analysis and travel mode choice in transportation systems;
  • Coordination and synchronization of transportation systems;
  • Relicense assessment and enhancement of transportation systems;
  • Disruption management in transportation systems;
  • Human factors and behavioral analysis in transportation systems;
  • Collaborative and cooperative systems in transportation;
  • Sustainable transportation planning and policy making;
  • Application of complex theory in emergency response and disaster management;
  • System engineering approaches to multimodal transportation networks;
  • Economic and environmental impact assessments of transportation systems;
  • Integration of renewable energy sources in transportation systems;
  • Advanced traffic prediction models using ai and machine learning;
  • Impact of autonomous vehicles on traffic dynamics and control;
  • Innovative materials and technologies for transportation infrastructure.

Dr. Shuqi Xue
Dr. Yun Wang
Dr. Xiaomeng Shi
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

  • system engineering
  • complex theory
  • transportation systems
  • transportation optimization
  • transportation control
  • transportation management
  • sustainable transportation
  • traffic dynamics
  • traffic behaviors
  • intelligent transportation

Published Papers (4 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

29 pages, 5960 KiB  
Article
Strategies for Humanitarian Logistics and Supply Chain in Organizational Contexts: Pre- and Post-Disaster Management Perspectives
by Amir Aghsami, Simintaj Sharififar, Nader Markazi Moghaddam, Ebrahim Hazrati, Fariborz Jolai and Reza Yazdani
Systems 2024, 12(6), 215; https://doi.org/10.3390/systems12060215 - 18 Jun 2024
Viewed by 707
Abstract
Every organization typically comprises various internal components, including regional branches, operations centers/field offices, major transportation hubs, and operational units, among others, housing a population susceptible to disaster impacts. Moreover, organizations often possess resources such as staff, various vehicles, and medical facilities, which can [...] Read more.
Every organization typically comprises various internal components, including regional branches, operations centers/field offices, major transportation hubs, and operational units, among others, housing a population susceptible to disaster impacts. Moreover, organizations often possess resources such as staff, various vehicles, and medical facilities, which can mitigate human casualties and address needs across affected areas. However, despite the importance of managing disasters within organizational networks, there remains a research gap in the development of mathematical models for such scenarios, specifically incorporating operations centers/field offices and external stakeholders as relief centers. Addressing this gap, this study examines an optimization model for both before and after disaster planning in a humanitarian supply chain and logistical framework within an organization. The affected areas are defined as regional branches, operational units, major transportation hubs, operations centers/field offices, external stakeholders, and medical facilities. A mixed-integer nonlinear model is formulated to minimize overall costs, considering factors such as penalty costs for untreated injuries and demand, delays in rescue and relief item distribution operations, and waiting costs for the injured in emergency medical vehicles and air ambulances. The model is implemented using GAMS software 47.1.0 for various test problems across different scales, with the Grasshopper Optimization Algorithm proposed for larger-scale scenarios. Numerical examples are provided to show the effectiveness and feasibility of the proposed model and to validate the metaheuristic approach. Sensitivity analysis is conducted to assess the model’s performance under different conditions, and key managerial insights and implications are discussed. Full article
(This article belongs to the Special Issue Application of System Engineering and Complex Theory in Transportation)
►▼ Show Figures

Figure 1

21 pages, 1726 KiB  
Article
Modeling a Multimodal Routing Problem with Flexible Time Window in a Multi-Uncertainty Environment
by Yan Ge, Yan Sun and Chen Zhang
Systems 2024, 12(6), 212; https://doi.org/10.3390/systems12060212 - 15 Jun 2024
Viewed by 379
Abstract
In this study, we extend the research on the multimodal routing problem by considering flexible time window and multi-uncertainty environment. A multi-uncertainty environment includes uncertainty regarding the demand for goods, the travel speed of the transportation mode, and the transfer time between different [...] Read more.
In this study, we extend the research on the multimodal routing problem by considering flexible time window and multi-uncertainty environment. A multi-uncertainty environment includes uncertainty regarding the demand for goods, the travel speed of the transportation mode, and the transfer time between different transportation modes. This environment further results in uncertainty regarding the delivery time of goods at their destination and the earliness and lateness caused by time window violations. This study adopts triangular fuzzy numbers to model the uncertain parameters and the resulting uncertain variables. Then, a fuzzy mixed integer nonlinear programming model is established to formulate the specific problem, including both fuzzy parameters and fuzzy variables. To make the problem easily solvable, this study employs chance-constrained programming and linearization to process the proposed model to obtain an equivalent credibilistic chance-constrained linear programming reformulation with an attainable global optimum solution. A numerical case study based on a commonly used multimodal network structure is presented to demonstrate the feasibility of the proposed method. Compared to hard and soft time windows, the numerical case analysis reveals the advantages of the flexible time window in reducing the total costs, avoiding low reliability regarding timeliness, and providing confidence level-sensitive route schemes to achieve flexible routing decision-making under uncertainty. Furthermore, the numerical case analysis verifies that it is necessary to model the multi-uncertainty environment to satisfy the improved customer requirements for timeliness and enhance the flexibility of the routing, and multimodal transportation is better than unimodal transportation when routing goods in an uncertain environment. The sensitivity analysis in the numerical case study shows the conflicting relationship between the economic objective and the reliability regarding the timeliness of the routing, and the result provides a reference for the customer to find a balance between them. Full article
(This article belongs to the Special Issue Application of System Engineering and Complex Theory in Transportation)
►▼ Show Figures

Figure 1

25 pages, 2727 KiB  
Article
Two-Stage Delivery System for Last Mile Logistics in Rural Areas: Truck–Drone Approach
by Debao Dai, Hanqi Cai, Liang Ye and Wei Shao
Systems 2024, 12(4), 121; https://doi.org/10.3390/systems12040121 - 6 Apr 2024
Viewed by 1412
Abstract
In rural areas of China, the challenges of efficient and cost-effective distribution are exacerbated by underdeveloped infrastructure and low population density, with last mile logistics distribution posing a significant obstacle. To address the gap in drone application for last mile logistics in rural [...] Read more.
In rural areas of China, the challenges of efficient and cost-effective distribution are exacerbated by underdeveloped infrastructure and low population density, with last mile logistics distribution posing a significant obstacle. To address the gap in drone application for last mile logistics in rural areas, a truck–drone distribution model was developed based on the specific conditions of rural regions. The improved fuzzy C-means algorithm (FCM) and genetic simulated annealing algorithm (GASA) were employed to tackle real−world cases in rural areas. The focus of the truck–drone system is to optimize the rural logistics distribution process, reduce delivery time, and minimize costs while considering factors such as maximum mileage of trucks and drones as well as customer priority. Compared to traditional methods, this system has demonstrated notable improvements in distribution efficiency and cost reduction, offering valuable insights for practical drone applications in last mile rural logistics. Full article
(This article belongs to the Special Issue Application of System Engineering and Complex Theory in Transportation)
►▼ Show Figures

Figure 1

20 pages, 6287 KiB  
Article
A Dynamic Collision Risk Assessment Model for the Traffic Flow on Expressways in Urban Agglomerations in North China
by Bing Li, Xiaoduan Sun, Yulong He and Meng Zhang
Systems 2024, 12(3), 86; https://doi.org/10.3390/systems12030086 - 6 Mar 2024
Viewed by 1174
Abstract
Expressways in urban agglomerations are important in connecting cities, thus attracting great attention from researchers in the expressways risk assessment. However, there is a lack of safety assessment models suitable for the characteristics of expressways in Chinese urban agglomerations, and the nature and [...] Read more.
Expressways in urban agglomerations are important in connecting cities, thus attracting great attention from researchers in the expressways risk assessment. However, there is a lack of safety assessment models suitable for the characteristics of expressways in Chinese urban agglomerations, and the nature and mode of dynamic risks on Chinese highways are still unclear. Therefore, this study adopts the Adaptive Neural Fuzzy Inference System (ANFIS) and the method of decision tree, combined with data from the Beijing section of the Beijing Harbin Expressway, to model the risk of accident-prone highways in urban agglomerations. To determine the optimal model, we evaluated the model’s bias at different time intervals. In addition, key factors affecting highway safety were analyzed, providing scientific support for the risk prevention of highways in urban agglomerations in China. Full article
(This article belongs to the Special Issue Application of System Engineering and Complex Theory in Transportation)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-4
Back to TopTop