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Axioms
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Advances in Fuzzy Logic and Multi-Criteria Decision Models
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Advances in Fuzzy Logic and Multi-Criteria Decision Models

A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Mathematical Analysis".

Deadline for manuscript submissions: closed (30 September 2024) | Viewed by 5282

Special Issue Editors

Dr. Amir Karbassi Yazdi

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Guest Editor
School of Engineering, Universidad Católica del Norte, Larrondo 1281, Coquimbo 1781421, Chile
Interests: MCDM; fuzzy sets; SCM; operations research
Dr. Fuli Zhou

E-Mail Website
Guest Editor
Department of Management Science & Engineering, College of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou 450002, China
Interests: city logistics; data-driven optimization; logistics informatization
Special Issues, Collections and Topics in MDPI journals
Dr. Yong Tan

E-Mail Website
Guest Editor
School of Management, University of Bradford, Bradford BD7 1DP, West Yorkshire, UK
Interests: performance evaluation; data envelopment analysis; financial economics; risk management; sustainable development; sustainability; banking; market structure; panel data analysis
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Thomas Hanne

E-Mail Website
Guest Editor
Institute for Information Systems, University of Applied Sciences and Arts Northwestern Switzerland, 4142 Münchenstein, Switzerland
Interests: computational intelligence; optimization simulation; multicriteria decision analysis; logistics and supply chain management; evolutionary computation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Making decisions is a critical component of many types of human activity. Achieving objectives requires making the right decisions. Over the past few decades, multi-criteria decision-making (MCDM) approaches have been successfully applied in a range of fields.

Due to this, MCDM is widely used for solving problems in different fields. A systematic and quantitative approach to addressing issues, MCDM provides several alternatives and several typically different criteria. Complex decisions, including business and real-life ones, require a decision-support system. Optimization is a decision-making process that aims to achieve the most effective results from the available resources. Multi-goal optimization is often necessary for real-world problems when constraints or discrete options are available.

Many industries use MCDM approaches to help decision-makers to make appropriate decisions. In many fields, they are becoming more popular. Business practice and decision-making theories contain many imprecise concepts. Imprecise data are used to build economic models, and imprecise data are used to inform decisions.

Complex business processes can be modeled using a variety of statistical and non-statistical decision-making techniques. Human decision-making is often suboptimal in predictable ways. Uncertainty, vagueness, and imprecision were modeled using fuzzy set theory. In both theoretical and practical studies, fuzzy sets contributed to economic progress. MCDM has greatly expanded beyond classical and formal methodologies. We welcome papers that integrate MCDM with uncertainty methods.

We welcome systemic solutions to practical decision making based on novel methodologies and tools. The latest methods can address multifaceted issues as well.

This Special Issue focuses on multi-criteria decision making, especially in multidisciplinary settings. High-quality papers are expected in categories such as discovery, integration, application, and teaching.

Original research and review articles can apply MCDM to real-life problems.

In addition to stimulating theoretical and applied research, this Special Issue should benefit MCDM and related fields. There are many articles to choose from in this Special Issue.

Dr. Amir Karbassi Yazdi
Dr. Fuli Zhou
Dr. Yong Tan
Prof. Dr. Thomas Hanne
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. Axioms 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

  • MCDM
  • SCM
  • fuzzy sets
  • fuzzy MCDM
  • application of fuzzy MCDM
  • group decision making

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Published Papers (3 papers)

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22 pages, 1523 KiB  
Article
Fermatean Hesitant Fuzzy Multi-Attribute Decision-Making Method with Probabilistic Information and Its Application
by Chuanyang Ruan, Xiangjing Chen and Lin Yan
Axioms 2024, 13(7), 456; https://doi.org/10.3390/axioms13070456 - 4 Jul 2024
Cited by 1 | Viewed by 818
Abstract
When information is incomplete or uncertain, Fermatean hesitant fuzzy sets (FHFSs) can provide more information to help decision-makers deal with more complex problems. Typically, determining attribute weights assumes that each attribute has a fixed influence. Introducing probability information can enable one to consider [...] Read more.
When information is incomplete or uncertain, Fermatean hesitant fuzzy sets (FHFSs) can provide more information to help decision-makers deal with more complex problems. Typically, determining attribute weights assumes that each attribute has a fixed influence. Introducing probability information can enable one to consider the stochastic nature of evaluation data and better quantify the importance of the attributes. To aggregate data by considering the location and importance degrees of each attribute, this paper develops a Fermatean hesitant fuzzy multi-attribute decision-making (MADM) method with probabilistic information and an ordered weighted averaging (OWA) method. The OWA method combines the concepts of weights and sorting to sort and weigh average property values based on those weights. Therefore, this novel approach assigns weights based on the decision-maker’s preferences and introduces probabilities to assess attribute importance under specific circumstances, thereby broadening the scope of information expression. Then, this paper presents four probabilistic aggregation operators under the Fermatean hesitant fuzzy environment, including the Fermatean hesitant fuzzy probabilistic ordered weighted averaging/geometric (FHFPOWA/FHFPOWG) operators and the generalized Fermatean hesitant fuzzy probabilistic ordered weighted averaging/geometric (GFHFPOWA/GFHFPOWG) operators. These new operators are designed to quantify the importance of attributes and characterize the attitudes of decision-makers using a probabilistic and weighted vector. Then, a MADM method based on these proposed operators is developed. Finally, an illustrative example of selecting the best new retail enterprise demonstrates the effectiveness and practicality of the method. Full article
(This article belongs to the Special Issue Advances in Fuzzy Logic and Multi-Criteria Decision Models)
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31 pages, 2224 KiB  
Article
An Integrated Multicriteria Sorting Methodology with q-Rung Orthopair Fuzzy Sets for Evaluating the Impacts of Delays on Residential Construction Projects
by Aure Flo Oraya, Hana Astrid Canseco-Tuñacao, Ryan Luciano, Aiza Patadlas, Ike Baguio, Joerabell Lourdes Aro, Fatima Maturan and Lanndon Ocampo
Axioms 2023, 12(8), 735; https://doi.org/10.3390/axioms12080735 - 27 Jul 2023
Cited by 5 | Viewed by 1894
Abstract
This study offers an integrated evaluation methodology for construction project delay causes viewed as a multicriteria sorting (MCS) problem. Time, cost, and quality were the three project management factors considered as criteria to evaluate 38 identified delay causes. The priority weights were extracted [...] Read more.
This study offers an integrated evaluation methodology for construction project delay causes viewed as a multicriteria sorting (MCS) problem. Time, cost, and quality were the three project management factors considered as criteria to evaluate 38 identified delay causes. The priority weights were extracted using the integration of Weighted Influence Non-linear Gauge Systems (WINGS) and Level-Based Weight Assessment (LBWA) to capture the inherent interdependencies of the criteria. The sorting of 38 delay causes was performed using FlowSort. To handle the uncertainty and vagueness of the judgments of the decision makers in the evaluation process, q-rung fuzzy orthopair fuzzy sets (q-ROFS) were integrated within the proposed computational framework. The proposed novel q-ROF–WINGS–LBWA–FlowSort method was applied in an actual case study in residential construction projects. The delay causes were categorized under three categories of construction firm vulnerability into four levels of impact. In highly vulnerable construction firms, thirty-five delay causes have a high impact, two have a moderate impact, and one has the least impact. In moderately vulnerable and least-vulnerable construction firms, 32 and 28 delay causes have a medium impact, respectively. The results may provide insights for decision makers in highly vulnerable construction firms, i.e., small companies with limited resources and networks. Layers of sensitivity and comparative analyses were put forward to test the robustness of the approach. Full article
(This article belongs to the Special Issue Advances in Fuzzy Logic and Multi-Criteria Decision Models)
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10 pages, 262 KiB  
Article
Axiomatic Processes for Asymmetric Allocation Rules under Fuzzy Multicriteria Situations
by Ling-Shan Chou, Hui-Chuan Wei, Ai-Tzu Li, Wei-Ni Wang and Yu-Hsien Liao
Axioms 2023, 12(3), 284; https://doi.org/10.3390/axioms12030284 - 8 Mar 2023
Viewed by 950
Abstract
The present paper is dedicated to investigating weighted allocation rules under fuzzy multicriteria situations. In real-world situations, participants may represent administrative departments of different natures in the management system; participants may be able to perform their duties in the economic model. In addition, [...] Read more.
The present paper is dedicated to investigating weighted allocation rules under fuzzy multicriteria situations. In real-world situations, participants may represent administrative departments of different natures in the management system; participants may be able to perform their duties in the economic model. In addition, participants may adopt relative operating levels to different situations and effectively engage multiple objectives under operational processes. Therefore, considering fuzzy behavior and multicriteria situations, it is reasonable to assign corresponding weights to participants and their relative behavior and to allocate efficiency according to weights in proportion to relative weights, even if it will lead to an asymmetrical situation. In existing studies on fuzzy allocation rules, weights are always given to “participants” or their “operating levels” and then the differences between participants and their operating levels are adjusted. Inspired by the above considerations, relative major results are as follows. (1) By simultaneously assigning weights to participants and their operating levels (strategies), this study seeks to use the supreme marginal variations among operating level vectors to define a new asymmetric allocation rule under fuzzy multicriteria situations. (2) This study further utilizes axiomatic results to illustrate the expedience for this weighted fuzzy asymmetric allocation rule. (3) Finally, an extended index is also proposed by replacing weights with the supreme marginal dedications. Full article
(This article belongs to the Special Issue Advances in Fuzzy Logic and Multi-Criteria Decision Models)
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