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Mathematics
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Recent Advances and Applications in Multi-Criteria Decision Analysis, 2nd Edition
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Recent Advances and Applications in Multi-Criteria Decision Analysis, 2nd Edition

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematics and Computer Science".

Deadline for manuscript submissions: closed (10 December 2022) | Viewed by 11912

Special Issue Editor

Prof. Dr. Antonio Jiménez-Martín

E-Mail Website
Guest Editor
Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Campus de Montegancedo S/N, Boadilla del Monte, 28660 Madrid, Spain
Interests: multi-attribute utility theory, group decision making; preference quantification; metaheuristics; simulation, risk analysis and management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Multi-criteria decision analysis (MCDA) techniques can be divided into two major groups. The first is discrete MCDA, including multi-attribute utility theory (MAUT), the analytic hierarchical process/analytic network process (AHP/ANP), and outranking methods, in which the decision-maker must evaluate a finite set of alternatives to a) select the best option, b) rank alternatives from the best to worst, and c) classify alternatives into predefined classes or the described options. The second is continuous MCDA, including multi-objective programming and goal programming, in which there is an infinite set of alternatives.

Over the last few decades, MCDA techniques have been successfully applied to complex decision-making problems in a wide range of fields, including economics, finance, logistics, environmental restoration, health, or industrial organization, to name but a few. Imprecision and uncertainty have been incorporated into the decision-making process and applied to group decision-making contexts.

The scope of this issue is MCDA in a broad sense, focusing on recent advances in both discrete and continuous techniques and significant applications in different fields.

As the title suggests, this Special Issue is a continuation of the Special Issue “Recent Advances and Applications in Multi-Criteria Decision Analysis” which has successfully included some excellent papers. We hope that this new Special Issue will attract the attention of more scholars who wish to publish their interesting insights here.

Prof. Dr. Antonio Jiménez-Martín
Guest Editor

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

  • multicritera decision-making (MCDM)
  • multiobjective optimization
  • preference quantification
  • uncertainty in decision-making
  • fuzzy MCDM
  • group decision-making and negotiation

Published Papers (6 papers)

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15 pages, 1448 KiB  
Article
Collaborative Decision Model for Allocating Intensive Care Units Beds with Scarce Resources in Health Systems: A Portfolio Based Approach under Expected Utility Theory and Bayesian Decision Analysis
by Eduarda Asfora Frej, Lucia Reis Peixoto Roselli, Alexandre Ramalho Alberti, Murilo Amorim Britto, Evônio de Barros Campelo Júnior, Rodrigo José Pires Ferreira and Adiel Teixeira de Almeida
Mathematics 2023, 11(3), 659; https://doi.org/10.3390/math11030659 - 28 Jan 2023
Cited by 3 | Viewed by 1015
Abstract
The COVID-19 pandemic has brought health systems to the brink of collapse in several regions around the world, as the demand for health care has outstripped the capacity of their services, especially regarding intensive care. In this context, health system managers have faced [...] Read more.
The COVID-19 pandemic has brought health systems to the brink of collapse in several regions around the world, as the demand for health care has outstripped the capacity of their services, especially regarding intensive care. In this context, health system managers have faced a difficult question: who should be admitted to an intensive care unit (ICU), and who should not? This paper addresses this decision problem using Expected Utility Theory and Bayesian decision analysis. In order to estimate the chances of survival for patients, a structured protocol has been proposed conjointly with physicians, based on the Sequential Organ Failure Assessment (SOFA) score. A portfolio selection approach is proposed to support tackling the ICU allocation problem. A simulation study shows that the proposed approach is more advantageous than other approaches already presented in the literature, with respect to the number of lives saved. The patients’ probabilities of survival inside and outside the ICU are important parameters of the model. However, assessing such probabilities can be a difficult task for health professionals. In order to give due treatment to the imprecise information regarding these probabilities, a Monte Carlo simulation is used to estimate the probabilities of recommending a patient be admitted to the ICU is the most appropriate decision, given the conditions presented. The methodology was implemented in an Information and Decision System called SIDTriagem, which is available online for free. With regards to managerial implications, SIDTriagem has a great potential to help in the response to public health emergencies systems as it facilitates rational decision-making regarding allocating ICU beds when resources are scarce. Full article
(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis, 2nd Edition)
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19 pages, 7557 KiB  
Article
Developing a Multicriteria Decision-Making Model Based on a Three-Layer Virtual Internet of Things Algorithm Model to Rank Players’ Value
by Che-Wei Chang
Mathematics 2022, 10(14), 2369; https://doi.org/10.3390/math10142369 - 06 Jul 2022
Cited by 3 | Viewed by 1743
Abstract
This paper proposes a multicriteria decision-making model based on a three-layer virtual internet of things (IoT) algorithm to automatically track and evaluate professional football players’ performance over the Internet. The three layers were respectively related to (1) automated data reading, (2) the players’ [...] Read more.
This paper proposes a multicriteria decision-making model based on a three-layer virtual internet of things (IoT) algorithm to automatically track and evaluate professional football players’ performance over the Internet. The three layers were respectively related to (1) automated data reading, (2) the players’ comprehensive grey relational degree calculation, and (3) the players’ classification. The methodology was applied in the context of the COVID-19 pandemic to investigate the performance of the top 10 defenders (according to The Sun, an internationally renowned sports website) in the European leagues, participating in the knockout phase of the 2019–20 UEFA Champions League. The results indicate that Virgil van Dijk of Liverpool FC was the best defender, followed by Harry Maguire of Manchester United, and Sergio Ramos of Real Madrid in the second and third positions, respectively. However, this ranking contradicted that of The Sun’s, which ranked these defenders in the seventh, tenth, and eighth positions, respectively. These results can help club management, coaches, and teams negotiate price positioning and future contract renewals or player transfers. Full article
(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis, 2nd Edition)
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21 pages, 3892 KiB  
Article
Sustainable Technology Supplier Selection in the Banking Sector
by Felipe Barrera, Marina Segura and Concepción Maroto
Mathematics 2022, 10(11), 1919; https://doi.org/10.3390/math10111919 - 03 Jun 2022
Cited by 5 | Viewed by 2085
Abstract
Sustainable supplier selection is a key strategic problem in supply chain management. The aim of this research is to provide a new hybrid multicriteria model for evaluating technology suppliers and validate it with a case study in the banking sector. This approach allows [...] Read more.
Sustainable supplier selection is a key strategic problem in supply chain management. The aim of this research is to provide a new hybrid multicriteria model for evaluating technology suppliers and validate it with a case study in the banking sector. This approach allows companies to perform qualification, selection, ranking and sorting of suppliers on a sustainable basis. Integration of several techniques is necessary to address this complex decision problem with conflicting economic, environmental and social criteria. Analytic hierarchy process (AHP) is useful for problem structuring and weighting criteria collaboratively. Multi-attribute utility theory (MAUT) is applied to obtain indicators for product quality and supplier risks, whose utility functions are derived by data-driven models that favour evaluation objectivity and transparency. Preference ranking organisation method for enrichment evaluation (PROMETHEE) is suitable for supplier selection due to its discriminant power among alternatives. Finally, FlowSort is proposed to classify suppliers into ordered groups and the outcomes are compared with results from MAUT. Results show its applicability by increasing process transparency and reducing operational risks in practice. Full article
(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis, 2nd Edition)
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33 pages, 2167 KiB  
Article
A Weighted Bonferroni-OWA Operator Based Cumulative Belief Degree Approach to Personnel Selection Based on Automated Video Interview Assessment Data
by Umut Asan and Ayberk Soyer
Mathematics 2022, 10(9), 1582; https://doi.org/10.3390/math10091582 - 07 May 2022
Cited by 2 | Viewed by 1871
Abstract
Asynchronous Video Interviewing (AVI) is considered one of the most recent and promising innovations in the recruitment process. Using AVI in combination with AI-based technologies enables recruiters/employers to automate many of the tasks that are typically required for screening, assessing, and selecting candidates. [...] Read more.
Asynchronous Video Interviewing (AVI) is considered one of the most recent and promising innovations in the recruitment process. Using AVI in combination with AI-based technologies enables recruiters/employers to automate many of the tasks that are typically required for screening, assessing, and selecting candidates. In fact, the automated assessment and selection process is a complex and uncertain problem involving highly subjective, multiple interrelated criteria. In order to address these issues, an effective and practical approach is proposed that is able to transform, weight, combine, and rank automated AVI assessments obtained through AI technologies and machine learning. The suggested approach combines Cumulative Belief Structures with the Weighted Bonferroni-OWA operator, which allows (i) aggregating assessment scores obtained in different forms and scales; (ii) incorporating interrelationships between criteria into the analysis (iii) considering accuracies of the learning algorithms as weights of criteria; and (iv) weighting criteria objectively. The proposed approach ensures a completely data-driven and efficient approach to the personnel selection process. To justify the effectiveness and applicability of the suggested approach, an example case is presented in which the new approach is compared to classical MCDM techniques. Full article
(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis, 2nd Edition)
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17 pages, 931 KiB  
Article
Approaching the Pareto Front in a Biobjective Bus Route Design Problem Dealing with Routing Cost and Individuals’ Walking Distance by Using a Novel Evolutionary Algorithm
by Herminia I. Calvete, Carmen Galé and José A. Iranzo
Mathematics 2022, 10(9), 1390; https://doi.org/10.3390/math10091390 - 21 Apr 2022
Cited by 2 | Viewed by 1363
Abstract
This paper addresses a biobjective bus routing problem that pays attention to both the routing cost and the total distance walked by the individuals to reach their assigned pickup point. These two objectives are conflicting. Generally, the less the individuals walk, the more [...] Read more.
This paper addresses a biobjective bus routing problem that pays attention to both the routing cost and the total distance walked by the individuals to reach their assigned pickup point. These two objectives are conflicting. Generally, the less the individuals walk, the more the number of visited pickup points and so the more the routing cost. In addition, the problem deals with finding the set of pickup points visited among the set of potential locations, identifying the set of individuals assigned to each visited pickup point, and designing the bus routes. Taking into account the highly combinatorial nature of the problem, an evolutionary algorithm is proposed to approach the associated Pareto front. Its main novelties are twofold. The first is the way in which the chromosomes are encoded since they only provide information about the number of routes and the visited pickup points. The second novelty lies in the procedure to construct a feasible solution from the chromosome, which involves a heuristic and several local search procedures to improve both objective functions. Computational experiments are carried out to check the performance of the algorithm in terms of the quality of the Pareto front yielded. Full article
(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis, 2nd Edition)
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22 pages, 2350 KiB  
Article
Evaluating Video Conferencing Software for Remote Working Using Two-Stage Grey MCDM: A Case Study from Vietnam
by Pham Ngoc Toan, Thanh-Tuan Dang and Le Thi Thu Hong
Mathematics 2022, 10(6), 946; https://doi.org/10.3390/math10060946 - 16 Mar 2022
Cited by 6 | Viewed by 2978
Abstract
The COVID-19 pandemic has completely changed the world, and businesses are struggling to create a new and effective working environment for their employees. Employees worldwide have moved from traditional face-to-face meetings to remote working using video conferencing software (VCS)—a powerful tool to support [...] Read more.
The COVID-19 pandemic has completely changed the world, and businesses are struggling to create a new and effective working environment for their employees. Employees worldwide have moved from traditional face-to-face meetings to remote working using video conferencing software (VCS)—a powerful tool to support companies during the pandemic and that can be an increasing trend in the future. For businesses who intend to adopt VCS for their organizations, choosing an appropriate platform can be an arduous task that requires the consideration of multiple criteria to save costs and optimize efficiency. In this paper, we propose a grey-based multi-criteria decision making (MCDM) framework that combines grey Analytical Hierarchy Process (G-AHP) and grey Evaluation Based on Distance from Average Solution (G-EDAS) methodologies, in which grey numbers are used to express the linguistic evaluation statements of experts. Initially, the evaluation criteria based on functionality, security, usability, technical performance, and pricing have been determined using a literature review and expert’s opinions to employ the MCDM approach. G-AHP was utilized to identify the criteria weights, and G-EDAS was then used to select the best VCS among the alternatives. A case illustration in Vietnam is presented to exhibit the proposed approach’s applicability. From the G-AHP findings, quality of video/audio, ease of use, mobile experience, number of participants allowed, and video recording capability have been ranked as the five most important criteria. From G-EDAS analysis, Microsoft Teams (VCS-03) was found to be the best. In addition, the robustness of the proposed model was tested by conducting sensitivity analysis and comparative analysis of methods, in which the priority rankings of the best VCSs are very similar. With the high demand for the trend of the remote working model, this study can be a basis for informed decisions to assist businesses in choosing their best-suited VCS to save costs and enhance productivity. Full article
(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis, 2nd Edition)
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