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Handling Preference Information for Multiple-Criteria Decision-Making: Theory and Applications in Management, Economics and Finance

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Multidisciplinary Applications".

Deadline for manuscript submissions: closed (30 October 2024) | Viewed by 1450

Special Issue Editors


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Guest Editor
Faculty of Economics and Finance, University of Bialystok, 15-062 Bialystok, Poland
Interests: negotiation; negotiation support; multi-criteria decision-making; fuzzy multi-criteria decision-making
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Operations Research, University of Economics in Katowice, 1 Maja 50, 40-287 Katowice, Poland
Interests: negotiation analysis; electronic negotiation; operations research; multiple-criteria decision-making

Special Issue Information

Dear Colleagues,

Making complex decisions based on multiple criteria affects all social and economic life disciplines. Hence, decision theory has developed numerous alternative methods for multiple-criteria decision support. These methods are based on preference information provided by the decision-maker, which can take various forms. This information may vary in terms of data representation: crisp, fuzzy, grey, taking into account uncertainty or imprecision, thereby necessitating the use of different algorithms for its processing, including those based on information theory and entropy. Preference information may be objective, based on actual data acquired by the decision-maker, or subjective, stemming from their expert assessment of the problem. It may also be provided by multiple decision-makers, requiring the need for consensus building, seeking common ground, or solving through game theoretical models. This diversity of preference information poses a challenge for modifying existing and developing new, often hybrid, multi-criteria decision-making (MCDM) methods.

Given the above, this Special Issue aims to present works that focus on various techniques of preference information analysis employed in individual and group multiple-criteria decision-making processes. Papers are welcome to be theoretical, addressing the development of methodologies, as well as applied, demonstrating the utilization of current and new MCDM techniques in solving real-life decision-making problems. We are particularly interested in applications in the sectors of management, economics, and finance. Topics include, but are not limited to, the following:

  • Methods of preference information analysis and processing;
  • Entropy and preference information;
  • Artificial intelligence and machine learning in preference analysis;
  • Analyzing and aggregating group preferences;
  • Game theory models with complex preference information;
  • New trends in MCDM methods for handling various preference information;
  • Objective preference information in MCDM;
  • Subjective preference information in MCDM;
  • Entropy-based MCDM;
  • Processing individual preferences in novel MCDM algorithms;
  • Methods for determining weights in MCDM problems;
  • Uncertainty and fuzziness in MCDM;
  • Preference information and decision support systems (DSS), negotiation support systems (NSS), and group decision support systems (GDSS).

Prof. Dr. Ewa Roszkowska
Prof. Dr. Tomasz Wachowicz
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. Entropy 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 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

  • preference information
  • preference analysis
  • weight determination
  • entropy
  • uncertainty
  • fuzziness
  • MCDM
  • fuzzy MCDM
  • group decision-making
  • machine learning
  • artificial intelligence
  • game theory
  • decision support systems

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Published Papers (1 paper)

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Research

22 pages, 1739 KiB  
Article
Approach Based on the Ordered Fuzzy Decision Making System Dedicated to Supplier Evaluation in Supply Chain Management
by Katarzyna Rudnik, Anna Chwastyk and Iwona Pisz
Entropy 2024, 26(10), 860; https://doi.org/10.3390/e26100860 - 12 Oct 2024
Cited by 1 | Viewed by 872
Abstract
The selection of suppliers represents a pivotal aspect of supply chain management and has a considerable impact on the success and competitiveness of the organization in question. The selection of a suitable supplier is a multi-criteria decision making (MCDM) problem based on a [...] Read more.
The selection of suppliers represents a pivotal aspect of supply chain management and has a considerable impact on the success and competitiveness of the organization in question. The selection of a suitable supplier is a multi-criteria decision making (MCDM) problem based on a number of qualitative, quantitative, and even conflicting criteria. The aim of this paper is to propose a novel MCDM approach dedicated to the supplier evaluation problem using an ordered fuzzy decision making system. This study uses a fuzzy inference system based on IF–THEN rules with ordered fuzzy numbers (OFNs). The approach employs the concept of OFNs to account for potential uncertainty and subjectivity in the decision making process, and it also takes into account the trends of changes in assessment values and entropy in the final supplier evaluation. This paper’s principal contribution is the development of a knowledge base and the demonstration of its application in an ordered fuzzy expert system for multi-criteria supplier evaluation in a dynamic and uncertain environment. The proposed system takes into account the dynamic changes in the value of assessment parameters in the overall supplier assessment, allowing for the differentiation of suppliers based on current and historical data. The utilization of OFNs in a fuzzy model then allows for a reduction in the complexity of the knowledge base in comparison to a classical fuzzy system and makes it more accessible to users, as it requires only basic arithmetic operations in the inference process. This paper presents a comprehensive framework for the assessment of suppliers against a range of criteria, including local hiring, completeness, and defect factors. Furthermore, the potential to integrate sustainability and ESG (environmental, social, and corporate governance) criteria in the assessment process adds value to the decision making framework by adapting to current trends in supply chain management. Full article
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