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Mathematics
Special Issues
Multi-Criteria Decision Making Methods and Their Applications
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Multi-Criteria Decision Making Methods and Their Applications

A special issue of Mathematics (ISSN 2227-7390).

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 15946

Special Issue Editors

Prof. Dr. Bartosz Sawik

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Guest Editor
Department of Business Informatics and Engineering Management, AGH University of Krakow, Krakow 30-059, Poland; Department of Statistics, Computer Science and Mathematics, Public University of Navarre, Pamplona 31006, Spain; Haas School of Business, University of California at Berkeley, Berkeley, CA 94720, USA.
Interests: operations engineering; multi-criteria optimization; decision sciences; green vehicle routing problems; portfolio optimization; computer science; conditional value-at-risk; logistics; supply chain; cybersecurity
Special Issues, Collections and Topics in MDPI journals
Dr. Elena Pérez-Bernabeu

E-Mail Website
Guest Editor
Department of Applied Statistics, Operations Research and Quality, Universitat Politècnica de València, 03801 Alcoy, Spain
Interests: operations engineering; multi-criteria optimization; decision sciences; green vehicle routing problems; portfolio optimization; computer science; conditional value-at-risk; logistics; supply chain; cybersecurity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The importance of strategic behavior in the human and social world is increasingly recognized in theory and practice. As a result, multi-criteria optimization methods, models and applications have emerged as a fundamental tool in pure and applied research. Multi-criteria decision making methods and optimization models and their applications strongly supports decision-making processes in an interactive environment. It draws on mathematics, economics, statistics, engineering, biology, political science, operations research, and other subjects. A multi-optimization occurs when multiple criteria considered by a decision maker is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. Decision maker considers a set of objectives in a situation in which each objective is possibly conflicting, possibly equally important, possibly overlapping. The problem is then to determine the trade off between objectives to support the decision making process.

The purpose of this Special Issue is to gather a collection of articles reflecting the latest developments in the mathematical programming methods of operations research for multi-criteria decision making processes for different fields of multi-criteria optimization approaches, models, applications and techniques. Submissions could cover not only multi-criteria theoretical algorithms, but also practical applications in logistics, supply chains, cybersecurity, healthcare and other area.

Prof. Dr. Bartosz Sawik
Prof. Dr. Elena Pérez-Bernabeu
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

  • multi-criteria decision making
  • mathematical programming
  • mixed integer programming
  • linear programming
  • quadratic programming
  • exact approach
  • approximation approaches
  • portfolio optimization
  • fair decision making
  • pareto frontier
  • goal programming
  • conditional value-at-risk
  • value-at-risk
  • weighting approach
  • lexicographic approach
  • reference point method
  • reference sets
  • fuzzy sets
  • heuristics

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Published Papers (6 papers)

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Research

20 pages, 1070 KiB  
Article
Fuzzy Method Based on the Removal Effects of Criteria (MEREC) for Determining Objective Weights in Multi-Criteria Decision-Making Problems
by Mohamad Shahiir Saidin, Lai Soon Lee, Siti Mahani Marjugi, Muhammad Zaini Ahmad and Hsin-Vonn Seow
Mathematics 2023, 11(6), 1544; https://doi.org/10.3390/math11061544 - 22 Mar 2023
Cited by 12 | Viewed by 2698
Abstract
In multi-criteria decision-making (MCDM) research, the criteria weights are crucial components that significantly impact the results. Many researchers have proposed numerous methods to establish the weights of the criterion. This paper provides a modified technique, the fuzzy method based on the removal effects [...] Read more.
In multi-criteria decision-making (MCDM) research, the criteria weights are crucial components that significantly impact the results. Many researchers have proposed numerous methods to establish the weights of the criterion. This paper provides a modified technique, the fuzzy method based on the removal effects of criteria (MEREC) by modifying the normalization technique and enhancing the logarithm function used to assess the entire performance of alternatives in the weighting process. Since MCDM problems intrinsically are ambiguous or complex, fuzzy theory is used to interpret the linguistic phrases into triangular fuzzy numbers. The comparative analyses were conducted through the case study of staff performance appraisal at a Malaysian academic institution and the simulation-based study is used to validate the effectiveness and stability of the presented method. The results of the fuzzy MEREC are compared with those from a few different objective weighting techniques based on the correlation coefficients, outlier tests and central processing unit (CPU) time. The results of the comparative analyses demonstrate that fuzzy MEREC weights are verified as the correlation coefficient values are consistent throughout the study. Furthermore, the simulation-based study demonstrates that even in the presence of outliers in the collection of alternatives, fuzzy MEREC is able to offer consistent weights for the criterion. The fuzzy MEREC also requires less CPU time compared to the existing MEREC techniques. Hence, the modified method is a suitable alternative and efficient for computing the objective criteria weights in the MCDM problems. Full article
(This article belongs to the Special Issue Multi-Criteria Decision Making Methods and Their Applications)
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27 pages, 2212 KiB  
Article
A Novel Axial-Distance-Based Aggregated Measurement (ADAM) Method for the Evaluation of Agri-Food Circular-Economy-Based Business Models
by Mladen Krstić, Giulio Paolo Agnusdei, Snežana Tadić, Milovan Kovač and Pier Paolo Miglietta
Mathematics 2023, 11(6), 1334; https://doi.org/10.3390/math11061334 - 9 Mar 2023
Cited by 17 | Viewed by 2738
Abstract
Multicriteria decision making (MCDM) is a field that helps decision makers evaluate alternatives based on multiple criteria and encompasses scoring, distance-based, pairwise comparison, and outranking methods. Recent developments have aimed to solve specific problems and overcoming the limitations of previous methods. This paper [...] Read more.
Multicriteria decision making (MCDM) is a field that helps decision makers evaluate alternatives based on multiple criteria and encompasses scoring, distance-based, pairwise comparison, and outranking methods. Recent developments have aimed to solve specific problems and overcoming the limitations of previous methods. This paper proposes a new axial-distance-based aggregated measurement (ADAM) method, which is used in combination with the best-worst method (BWM) to evaluate agri-food circular economy (CE)-based business models (BMs) to create a more sustainable and efficient system for producing and consuming food. This paper proposes nine BMs, which were evaluated against eight criteria. The BWM method was used to obtain the criteria weights, while the ADAM method was used to obtain a final ranking of the BMs. The results indicate that a sustainable circular agri-food supply chain is a BM that can bring companies the most significant progress in business and strengthen their position in the market. We concluded that the ADAM method is effective for solving MCDM problems and that, overall, the model is an effective tool for solving the problem defined in this study. The main contributions are the development of a new MCDM method and a hybrid model, the establishment of the framework for evaluation and selection of CE-based BMs, and the identification of the most important ones. Full article
(This article belongs to the Special Issue Multi-Criteria Decision Making Methods and Their Applications)
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28 pages, 665 KiB  
Article
Avoiding the Worst Decisions: A Simulation and Experiment
by Kazuhisa Takemura, Yuki Tamari and Takashi Ideno
Mathematics 2023, 11(5), 1165; https://doi.org/10.3390/math11051165 - 27 Feb 2023
Cited by 2 | Viewed by 2469
Abstract
Many practical decisions are more realistic concerning preventing bad decisions than seeking better ones. However, there has been no behavioral decision theory research on avoiding the worst decisions. This study is the first behavioral decision research on decision strategies from the perspective of [...] Read more.
Many practical decisions are more realistic concerning preventing bad decisions than seeking better ones. However, there has been no behavioral decision theory research on avoiding the worst decisions. This study is the first behavioral decision research on decision strategies from the perspective of avoiding the worst decisions. We conducted a computer simulation with the Mersenne Twister method and a psychological experiment using the monitoring information acquisition method for two-stage decision strategies of all combinations for different decision strategies: lexicographic, lexicographic semi-order, elimination by aspect, conjunctive, disjunctive, weighted additive, equally weighted additive, additive difference, and a majority of confirming dimensions. The rate of choosing the least expected utility value among the alternatives was computed as the rate of choosing the worst alternative in each condition. The results suggest that attention-based decision rules such as disjunctive strategy lead to a worse decision, and that striving to make the best choice can conversely often lead to the worst outcome. From the simulation and the experiment, we concluded that simple decision strategies such as considering what is most important can lead to avoiding the worst decisions. The findings of this study provide practical implications for decision support in emergency situations. Full article
(This article belongs to the Special Issue Multi-Criteria Decision Making Methods and Their Applications)
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18 pages, 2055 KiB  
Article
Criteria Weights in Hiring Decisions—A Conjoint Approach
by Monica Mihaela Maer Matei, Ana-Maria Zamfir and Cristina Mocanu
Mathematics 2023, 11(3), 728; https://doi.org/10.3390/math11030728 - 1 Feb 2023
Cited by 1 | Viewed by 2122
Abstract
Understanding human behavior in the decision-making process represents a challenge for researchers in the socio-economic field. The complexity comes from multiple criteria acting simultaneously. Hiring decisions are made on a set of criteria representing the attributes of the applicants. This study’s main objective [...] Read more.
Understanding human behavior in the decision-making process represents a challenge for researchers in the socio-economic field. The complexity comes from multiple criteria acting simultaneously. Hiring decisions are made on a set of criteria representing the attributes of the applicants. This study’s main objective is to investigate Romanian employers’ behavior when recruiting for jobs targeting graduates from economic studies. The method used to identify the weights employers assign to different skills was based on an experimental technique-choice based conjoint. A survey experiment was conducted to produce causal conclusions about the recruiting process. The estimation was performed with a methodology based on machine learning, which allows to investigate interactions between subjects’ characteristics and conjoint criteria. The findings of our experiment align with other studies pointing to the increased relevance of non-cognitive skills for employability. Additionally, our results show that criteria weights in hiring decisions depend on company size, ownership, activity sector or personal characteristics of the recruiter. Our research provides a mechanism for understanding employers’ perspectives. This is valuable for informing job seekers to adjust their job search strategies and to invest in the skills offering hiring opportunities. Moreover, universities can use the results to adapt their educational programs to labor market needs. Full article
(This article belongs to the Special Issue Multi-Criteria Decision Making Methods and Their Applications)
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11 pages, 2102 KiB  
Article
Formulation of a Grey Sequence and an Optimization Solution to Present Multi-Layer Family Networks
by Shahryar Sorooshian
Mathematics 2023, 11(1), 144; https://doi.org/10.3390/math11010144 - 28 Dec 2022
Cited by 2 | Viewed by 1367
Abstract
Despite the potential benefits of family relationships and family events, insufficient studies have been undertaken to address how to overcome their obstacles. So, the main objective of this paper is to present a systematic model for prioritizing family members in response to standing [...] Read more.
Despite the potential benefits of family relationships and family events, insufficient studies have been undertaken to address how to overcome their obstacles. So, the main objective of this paper is to present a systematic model for prioritizing family members in response to standing limitations on family relationships. For this, the chosen methodology is conceptual sequence modeling, and the proposed model is optimized to include family membership motives and demotivators. Moreover, multiple criteria for the membership nominations are included to respond to the dynamic scenarios and complexity of decision-making. The feasibility of the proposed model is proven in a numerical case. Thus, the contribution of the proposed model is predictable to be from event planning to relative relationship management. Full article
(This article belongs to the Special Issue Multi-Criteria Decision Making Methods and Their Applications)
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23 pages, 2664 KiB  
Article
An Industrial Blockchain-Based Multi-Criteria Decision Framework for Global Freight Management in Agricultural Supply Chains
by Dilupa Nakandala, Yung Po Tsang, Henry Lau and Carman Ka Man Lee
Mathematics 2022, 10(19), 3550; https://doi.org/10.3390/math10193550 - 29 Sep 2022
Cited by 7 | Viewed by 2457
Abstract
In view of increasing supply chain disruption events, for example the China–United States trade war, the COVID-19 pandemic, and the Russia–Ukraine war, the complexity and dynamicity of global freight management keeps increasing. To build a resilient and sustainable supply chain, industrial practitioners are [...] Read more.
In view of increasing supply chain disruption events, for example the China–United States trade war, the COVID-19 pandemic, and the Russia–Ukraine war, the complexity and dynamicity of global freight management keeps increasing. To build a resilient and sustainable supply chain, industrial practitioners are eager to systematically revamp the freight management decision process related to the selection of carriers, shipping lanes, and third-party logistics service providers. Therefore, this study aims at strengthening decision-making capabilities for global freight management, in which an industrial blockchain-based global freight decision framework (IB-GFDF) is proposed to incorporate consortium blockchain technology with the Bayesian best-worst method. Through the blockchain technology, pairwise comparisons can be conducted over the international freight network in a decentralized and immutable manner, and thus, a secure and commonly agreed-on pairwise comparison dataset is acquired. Subsequently, the pairwise comparison dataset with multi-stakeholder opinions is analyzed using the Bayesian best-worst method in order to prioritize the selection decision criteria related to carriers, shipping lanes, and 3PL service providers for global freight management. To verify the methodological feasibility, a case study of an Australian agricultural supply chain firm was conducted to support the development end-to-end (E2E) supply chain solutions originated from Australia. It was found that port infrastructure, ports of call and communication effectiveness were the major criteria for the selection decision, which can be emphasized in future global freight collaboration. In addition, an immutable and append-only record of pairwise comparisons can be established to support the visibility of time-varying stakeholders’ preferences. Full article
(This article belongs to the Special Issue Multi-Criteria Decision Making Methods and Their Applications)
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