Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.8
3.9
Journals
Sustainability
Special Issues
Sustainable Transportation and City Integrated Emergency Response Science
sustainability-logo
Submit to Sustainability Review for Sustainability Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Sustainable Transportation and City Integrated Emergency Response Science

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: closed (1 May 2023) | Viewed by 5303

Special Issue Editors

Dr. Xiaobing Yu

E-Mail Website
Guest Editor
School of Management and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
Interests: emergency management; disaster analysis; operation research and optimization
Prof. Dr. Mei Cai

E-Mail Website
Guest Editor
School of Management and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
Interests: disaster management; risk assessment theory and technology
Dr. Jie Li

E-Mail Website
Guest Editor
National Science Library, Chinese Academy of Sciences, Beijing 100190, China
Interests: safety science; emergency management; mapping knowledge domains
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Sustainable transportation is commonly referred to as ‘Green Transportation’, which is the entails a means of transportation that is safe and has a low impact on the environment and climate. Sustainable transportation makes use of renewable energy rather than coal, petroleum, or other fossil fuels that negatively affect the Earth. Meanwhile, the world is becoming increasingly globalized and connected, with rapidly advancing technologies and changing weather patterns. Critical infrastructures and social structures are threatened by natural and manmade disasters, especial in big cities. These disasters have brought destructive damage to infrastructures and people’s lives all over the world. City-integrated emergency response systems are thus essential. Emergency management is the organization and management of resources and responsibilities in emergencies (preparedness, response, mitigation, and recovery). The aim is to reduce the harmful effects of disasters.

Recent research has made considerable contributions to the development of sustainable transportation and emergency management. This Special Issue aims to share and discuss the latest developments in these areas, inviting prospective authors to contribute research papers on related topics.  High-quality research presenting original and unpublished results of empirical, model, algorithm, or theoretical work in all areas of sustainable transportation and emergency management are especially encouraged.

Original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Sustainable transportation;
  • Green transportation;
  • Travel pollution;
  • Carbon dioxide emissions;
  • Monitoring, prediction, and warning;
  • Disaster risk analysis;
  • Disaster decision making;
  • Disaster emergency optimization;
  • Disaster risk reduction.

Dr. Xiaobing Yu
Prof. Dr. Mei Cai
Dr. Jie Li
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. Sustainability 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 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

  • sustainable transportation
  • emergency management
  • city disaster

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

31 pages, 12841 KiB  
Article
A Hybrid Brain Storm Optimization Algorithm to Solve the Emergency Relief Routing Model
by Xuming Wang, Jiaqi Zhou, Xiaobing Yu and Xianrui Yu
Sustainability 2023, 15(10), 8187; https://doi.org/10.3390/su15108187 - 17 May 2023
Cited by 3 | Viewed by 1109
Abstract
Due to the inappropriate or untimely distribution of post-disaster goods, many regions did not receive timely and efficient relief for infected people in the coronavirus disease outbreak that began in 2019. This study develops a model for the emergency relief routing problem (ERRP) [...] Read more.
Due to the inappropriate or untimely distribution of post-disaster goods, many regions did not receive timely and efficient relief for infected people in the coronavirus disease outbreak that began in 2019. This study develops a model for the emergency relief routing problem (ERRP) to distribute post-disaster relief more reasonably. Unlike general route optimizations, patients’ suffering is taken into account in the model, allowing patients in more urgent situations to receive relief operations first. A new metaheuristic algorithm, the hybrid brain storm optimization (HBSO) algorithm, is proposed to deal with the model. The hybrid algorithm adds the ideas of the simulated annealing (SA) algorithm and large neighborhood search (LNS) algorithm into the BSO algorithm, improving its ability to escape from the local optimum trap and speeding up the convergence. In simulation experiments, the BSO algorithm, BSO+LNS algorithm (combining the BSO with the LNS), and HBSO algorithm (combining the BSO with the LNS and SA) are compared. The results of simulation experiments show the following: (1) The HBSO algorithm outperforms its rivals, obtaining a smaller total cost and providing a more stable ability to discover the best solution for the ERRP; (2) the ERRP model can greatly reduce the level of patient suffering and can prioritize patients in more urgent situations. Full article
(This article belongs to the Special Issue Sustainable Transportation and City Integrated Emergency Response Science)
►▼ Show Figures

Figure 1

21 pages, 6779 KiB  
Article
A Behavior Change Mining Method Based on Complete Logs with Hidden Transitions and Their Applications in Disaster Chain Risk Analysis
by Shuya Sun and Qingsheng Li
Sustainability 2023, 15(2), 1655; https://doi.org/10.3390/su15021655 - 14 Jan 2023
Viewed by 1145
Abstract
The aim of change mining is to discover changes in process models based on execution data recorded in event logs. There may be hidden transitions in the process models related to, for example, business integration and user requirements that do not exist in [...] Read more.
The aim of change mining is to discover changes in process models based on execution data recorded in event logs. There may be hidden transitions in the process models related to, for example, business integration and user requirements that do not exist in event logs. Behavioral change mining in the case of hidden transitions is a fundamental problem in the field of change mining. Existing research on change mining has not considered the effects of hidden transitions. This paper proposes a novel method based on complete logs with hidden transitions for mining behavioral changes. We analyze the behavioral relations of activities based on changed logs under the condition that the original model is unknown. Log-driven change mining is realized by calculating the log behavioral profile, minimum successor relation, and log-weighted coefficient, which allows the mining of hidden transitions, as well as changed behavioral relations. Finally, this method is applied to disaster chain risk analysis, and the evolution of disaster chains in different scenarios is mined from disaster logs to determine the type of disaster chain. The results of this paper provide a scientific basis for the strategy of chain-cutting disaster mitigation in the emergency management of disaster chains. Full article
(This article belongs to the Special Issue Sustainable Transportation and City Integrated Emergency Response Science)
►▼ Show Figures

Figure 1

33 pages, 2236 KiB  
Article
A Dynamic Social Network Matching Model for Virtual Power Plants and Distributed Energy Resources with Probabilistic Linguistic Information
by Mei Cai, Suqiong Hu, Ya Wang and Jingmei Xiao
Sustainability 2022, 14(22), 14920; https://doi.org/10.3390/su142214920 - 11 Nov 2022
Cited by 1 | Viewed by 1212
Abstract
Virtual power plants (VPPs) offer an effective means to address the imbalance issue between electricity supply and demand to advance the world’s low-carbon development. To fully utilize the limited resources in the virtual power plant planning stage, a two-sided match between VPPs and [...] Read more.
Virtual power plants (VPPs) offer an effective means to address the imbalance issue between electricity supply and demand to advance the world’s low-carbon development. To fully utilize the limited resources in the virtual power plant planning stage, a two-sided match between VPPs and distributed energy companies is needed to better implement resource aggregation management. Because of the vagueness in this matching environment, the probabilistic linguistic term set (PLTS) is necessary to apply to express the decision makers’ preference. Considering the complex social relationships and intense competition among companies, a dynamic social network two-sided matching model is proposed for solving the multi-attribute two-sided matching decision-making problem. Firstly, we present a matching satisfaction degree described by PLTS. A dynamic social trust degree based on the sliding time concept is proposed. Secondly, the social trust network relationships are built based on the direct and indirect dynamic trust degree among companies. This relationship is then combined with an improved trust rank algorithm to identify the most authoritative and the most trusted company to provide the target company with a recommendation for the next moment. Besides, given that companies compete for limited resources, we further define the competitive satisfaction degree and apply the two-sided matching model. Additionally, then a two-sided matching model is developed. Finally, our model is tested numerically to ensure its accuracy and reliability. Full article
(This article belongs to the Special Issue Sustainable Transportation and City Integrated Emergency Response Science)
►▼ Show Figures

Figure 1

10 pages, 1575 KiB  
Article
Flood Disaster Risk Assessment Based on DEA Model in Southeast Asia along “The Belt and Road”
by Xuming Wang, Xianrui Yu and Xiaobing Yu
Sustainability 2022, 14(20), 13145; https://doi.org/10.3390/su142013145 - 13 Oct 2022
Cited by 3 | Viewed by 1325
Abstract
The “Belt and Road” initiative proposed by China has received much attention from the international community. Natural disasters along the route have posed considerable challenges to the “Belt and Road” economic construction. Southeast Asia, as the main thoroughfare of the Maritime Silk Road, [...] Read more.
The “Belt and Road” initiative proposed by China has received much attention from the international community. Natural disasters along the route have posed considerable challenges to the “Belt and Road” economic construction. Southeast Asia, as the main thoroughfare of the Maritime Silk Road, always suffers from floods. It is necessary to evaluate flood risk to enhance disaster emergency management. Based on the Data Envelopment Analysis (DEA) model, inputs consist of four factors: the number of deaths, victims, frequency of occurrence, and economic losses caused by meteorological disasters. To study the vulnerability to flood disasters in Southeast Asian countries, the four factors caused by flood disasters were taken as outputs, respectively. The relative efficiency values of Laos, Malaysia and Cambodia exceed 0.8. They are most vulnerable to floods. The following four countries, Thailand, Myanmar, Indonesia, and the Philippines, are also vulnerable to flood disasters. The vulnerability of Vietnam is relatively lower than the others. In brief, the risk of flood disasters in Southeast Asia is high. Risk assessment for Southeast Asia is essential to ensure the implementation of the “Belt and Road” initiative. Full article
(This article belongs to the Special Issue Sustainable Transportation and City Integrated Emergency Response Science)
►▼ 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