Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.0
2.3
Journals
Mathematics
Special Issues
Multi-Criteria Decision Making Under Uncertainty
share announcement

Multi-Criteria Decision Making Under Uncertainty

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D2: Operations Research and Fuzzy Decision Making".

Deadline for manuscript submissions: 10 January 2026 | Viewed by 1818

Special Issue Editors

Dr. Liang Wang

E-Mail Website
Guest Editor
Decision Sciences Institute, Fuzhou University, Fuzhou 350025, China
Interests: decision theory and methods; emergency decision making
Special Issues, Collections and Topics in MDPI journals
Dr. Alvaro Labella

E-Mail Website
Guest Editor
Department of Computer Science, University of Jaen, 23071 Jaen, Spain
Interests: decision theory and methods; consensus-reaching processes; decision support systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In today’s complex and dynamic world, decision making often involves multiple conflicting criteria and operates under significant uncertainty. Whether in fields such as engineering, economics, healthcare, environmental management, or public policy, decision makers frequently encounter situations where they must evaluate numerous alternatives based on various performance metrics, all while accounting for uncertain and fluctuating conditions.

This Special Issue aims to bring together the latest research, methodologies, and applications in this crucial and challenging area.

Potential topics include but are not limited to:

  • Handling fuzzy information in multi-criteria decision making;
  • Large-scale group decision making;
  • Consensus reaching process;
  • Multi-criteria sorting;
  • Emergency decision making;
  • Emergency early warning;
  • Risk analysis.

Dr. Liang Wang
Dr. Alvaro Labella
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. 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

  • large-scale group decision making
  • consensus reaching process
  • multi-criteria sorting
  • emergency decision making
  • emergency early warning
  • risk analysis

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

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

Published Papers (2 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

28 pages, 2969 KiB  
Article
Hesitant Fuzzy Consensus Reaching Process for Large-Scale Group Decision-Making Methods
by Wei Liang, Álvaro Labella, Meng-Jun Meng, Ying-Ming Wang and Rosa M. Rodríguez
Mathematics 2025, 13(7), 1182; https://doi.org/10.3390/math13071182 - 3 Apr 2025
Viewed by 275
Abstract
The emergence and popularity of social media have made large-scale group decision-making (LSGDM) problems increasingly common, resulting in significant research interest in this field. LSGDM involves numerous evaluators, which can lead to disagreements and hesitancy among them. Hesitant fuzzy sets (HFSs) become crucial [...] Read more.
The emergence and popularity of social media have made large-scale group decision-making (LSGDM) problems increasingly common, resulting in significant research interest in this field. LSGDM involves numerous evaluators, which can lead to disagreements and hesitancy among them. Hesitant fuzzy sets (HFSs) become crucial in this context as they capture the uncertainty and hesitancy among evaluators. On the other hand, research on the Consensus Reaching Process (CRP) becomes particularly important in dealing with the inevitable differences among the great number of evaluators. Ways to mitigate these differences to reach an agreement are a crucial area of study. For this reason, this paper presents a new CRP model to deal with LSGDM problems in hesitant fuzzy environments. First, HFSs and Normal-type Hesitant Fuzzy Sets (N-HFSs) are introduced to integrate evaluators’ subgroup and collective opinions, aiming to preserve as much decision information as possible while reducing computational complexity. Subsequently, a CRP with a detailed feedback suggestion generation mechanism is developed, which considers the willingness of evaluators to modify their opinions, thereby improving the effectiveness of reaching an agreement. Finally, a LSGDM framework that does not require any normalization process is proposed, and its feasibility and robustness are demonstrated through a numerical example. Full article
(This article belongs to the Special Issue Multi-Criteria Decision Making Under Uncertainty)
►▼ Show Figures

Figure 1

25 pages, 523 KiB  
Article
Staged Resource Allocation Optimization under Heterogeneous Grouping Based on Interval Data: The Case of China’s Forest Carbon Sequestration
by Nan Wu, Mengjiao Zhang, Yan Huang and Jiawei Wang
Mathematics 2024, 12(17), 2650; https://doi.org/10.3390/math12172650 - 26 Aug 2024
Cited by 1 | Viewed by 990
Abstract
In interval data envelopment analysis (DEA), the production possibility set is variable, which causes traditional resource allocation optimization methods to yield results with limited reachability. This study aims to improve existing resource allocation optimization models so that they can produce meaningful results when [...] Read more.
In interval data envelopment analysis (DEA), the production possibility set is variable, which causes traditional resource allocation optimization methods to yield results with limited reachability. This study aims to improve existing resource allocation optimization models so that they can produce meaningful results when handling interval data. Addressing this topic can enhance the applicability of existing models and improve decision-making accuracy. We grouped decision-making units (DMUs) based on heterogeneity to form production possibility sets. We then considered the characteristics of the worst and best production possibility sets in the interval DEA to establish multiple benchmark fronts. A staged optimization procedure is proposed; the procedure provides a continuous optimization solution, offering a basis for decision-makers to formulate strategies. To illustrate this, we provide a numerical example analysis and a case study on forest carbon sequestration. Finally, by applying our method to China’s forest carbon sink data, we show that it better meets the practical needs in China. The practical implication of this procedure is that it provides a basis for decision makers to formulate strategies based on interval data. The theoretical implication is that it extends the application of DEA models to interval data. Full article
(This article belongs to the Special Issue Multi-Criteria Decision Making Under Uncertainty)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop