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Recent Advances and Applications in Multi-Criteria Decision Analysis

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

Deadline for manuscript submissions: closed (28 February 2021) | Viewed by 27998

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Special Issue Editor

Prof. Dr. Antonio Jiménez-Martín

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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
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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), analytic hierarchical process/analytic network process (AHP/ANP), and outranking methods, where the decision-maker has to 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, where 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, such as economics, finance, logistics, environmental restoration, health or industrial organization, to name but a few, and 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.

Prof. Dr. Antonio Jiménez-Martín
Guest Editor

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Keywords

discrete and continuous MCDA
preference quantification
uncertainty in decision-making
group decision-making

Published Papers (12 papers)

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Editorial

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3 pages, 191 KiB

Open AccessEditorial

Special Issue “Recent Advances and Applications in Multi Criteria Decision Analysis”

by Antonio Jiménez-Martín

Mathematics 2022, 10(13), 2343; https://doi.org/10.3390/math10132343 - 04 Jul 2022

Viewed by 1137

Abstract

Over the last few decades, Multi-criteria Decision Analysis (MCDA) techniques have been successfully applied to complex decision-making problems in a wide range of fields, such as economics, finance, logistics, environmental restoration, health or industrial organization, to name but a few, and imprecision and [...] Read more.

(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis)

Research

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21 pages, 974 KiB

Open AccessArticle

A Hybrid Strategic Oscillation with Path Relinking Algorithm for the Multiobjective k-Balanced Center Location Problem

by Jesús Sánchez-Oro, Ana D. López-Sánchez, Anna Martínez-Gavara, Alfredo G. Hernández-Díaz and Abraham Duarte

Mathematics 2021, 9(8), 853; https://doi.org/10.3390/math9080853 - 14 Apr 2021

Cited by 4 | Viewed by 1620

Abstract

This paper presents a hybridization of Strategic Oscillation with Path Relinking to provide a set of high-quality nondominated solutions for the Multiobjective k-Balanced Center Location problem. The considered location problem seeks to locate k out of m facilities in order to serve n demand points, minimizing the maximum distance between any demand point and its closest facility while balancing the workload among the facilities. An extensive computational experimentation is carried out to compare the performance of our proposal, including the best method found in the state-of-the-art as well as traditional multiobjective evolutionary algorithms. Full article

(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis)

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18 pages, 1252 KiB

Open AccessArticle

Aluminium Parts Casting Scheduling Based on Simulated Annealing

by Antonio Jiménez-Martín, Alfonso Mateos and Josefa Z. Hernández

Mathematics 2021, 9(7), 741; https://doi.org/10.3390/math9070741 - 31 Mar 2021

Cited by 4 | Viewed by 1699

Abstract

This paper focuses on the last stage of the aluminium production process in the context of Industry 4.0: schedule optimization in the casting process. Casting is one of the oldest manufacturing processes in which a liquid material is usually poured into a mold that contains a hollow cavity of the desired shape and then allowed to solidify. This is a complex scheduling problem in which several constraints, such as different maintenance processes, maximum stocks, machine breakdowns, work shifts, or the maximum number of mold changes per day, come into play. Four objective functions have to be taken into account simultaneously. We have to minimize both the unmet demand at the end of the schedule, and the delays in the injection process with regard to daily demands. Production costs, including the cost of electricity consumption in the injection process and gas consumption associated with melting furnaces, should be minimized. Finally, the total number of mold changes throughout the schedule must also be reduced to a minimum. The simulated annealing (SA) metaheuristic has been adapted to solve this complex optimization process and parameterized for application to a wide variety of aluminium making processes. SA efficiently solves the problem and provides an optimal solution in about three minutes. Full article

(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis)

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16 pages, 318 KiB

Open AccessArticle

A Multicriteria Extension of the Efficient Market Hypothesis

by Francisco Salas-Molina, David Pla-Santamaria, Fernando Mayor-Vitoria and Maria Luisa Vercher-Ferrandiz

Mathematics 2021, 9(6), 649; https://doi.org/10.3390/math9060649 - 18 Mar 2021

Cited by 2 | Viewed by 1711

Abstract

Challenging the Efficient Market Hypothesis (EMH) has been a recurrent topic for researchers and practitioners since its formulation. Hundreds of empirical studies claim to either prove or disprove the EMH by means of a number of heterogeneous methods. Even though the EMH is usually adjusted to a measure of risk, there is a lack of a formal analysis within a multiple-criteria context. In this paper, we propose a extension of the EMH that accommodates the foundations of multiple-criteria decision analysis. To this end, we rely on a family of parametric signed dissimilarity measures to assess multidimensional performance differences. Since normalization is a critical step in our approach to avoid meaningless comparisons, we present two novel theoretical results connecting different normalization techniques. This multicriteria extension provides a common framework on which to add empirical evidence regarding the EMH testing. Full article

(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis)

17 pages, 1194 KiB

Open AccessArticle

A Multicriteria Goal Programming Model for Ranking Universities

by Fernando García, Francisco Guijarro and Javier Oliver

Mathematics 2021, 9(5), 459; https://doi.org/10.3390/math9050459 - 24 Feb 2021

Cited by 7 | Viewed by 1911

Abstract

This paper proposes the use of a goal programming model for the objective ranking of universities. This methodology has been successfully used in other areas to analyze the performance of firms by focusing on two opposite approaches: (a) one favouring those performance variables that are aligned with the central tendency of the majority of the variables used in the measurement of the performance, and (b) an alternative one that favours those different, singular, or independent performance variables. Our results are compared with the ranking proposed by two popular World University Rankings, and some insightful differences are outlined. We show how some top-performing universities occupy the best positions regardless of the approach followed by the goal programming model, hence confirming their leadership. In addition, our proposal allows for an objective quantification of the importance of each variable in the performance of universities, which could be of great interest to decision-makers. Full article

(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis)

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15 pages, 3378 KiB

Open AccessArticle

A Multiobjective Model for Analysis of the Relationships between Military Expenditures, Security, and Human Development in NATO Countries

by Patricio Vallejo-Rosero, M. Carmen García-Centeno, Laura Delgado-Antequera, Osvaldo Fosado and Rafael Caballero

Mathematics 2021, 9(1), 23; https://doi.org/10.3390/math9010023 - 24 Dec 2020

Cited by 2 | Viewed by 1904

Abstract

The aim of this work is to design a multiobjective model to explain the behavior among military expenditures (MEs), the human development index, and the global peace index in countries belonging to the North Atlantic Treaty Organization (NATO) for the study period 2008–2016. In order to solve this problem, different decision variables have been considered: health expenditure, education expenditure, Gross Domestic Product (GDP), collected taxes, public debt, and R&D costs, which are related to health, education, and economic sectors. To determine the relationships among decision variables making up the objective functions and model constraints, different panel data models were estimated. The obtained results show that the major part of the NATO countries present a behavior which differs from what is efficient. In this context, this work highlights the path to follow by each country, such as the implementation of public budget policies in the health and education sectors, and for collected taxes and public debt, to achieve efficient solutions. Full article

(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis)

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19 pages, 1242 KiB

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A Failure Mode Assessment Model Based on Neutrosophic Logic for Switched-Mode Power Supply Risk Analysis

by James J. H. Liou, Perry C. Y. Liu and Huai-Wei Lo

Mathematics 2020, 8(12), 2145; https://doi.org/10.3390/math8122145 - 01 Dec 2020

Cited by 10 | Viewed by 2216

Abstract

Reducing the potential risks in the manufacturing process to improve the reliability of the switched-mode power supply (SMPS) is a critical issue for the users’ safety. This paper proposes a novel failure mode and effects analysis (FMEA) model based on hybrid multiple criteria decision-making (MCDM), which adopts neutrosophic set theory into the proposed model. A developed neutrosophic Best Worst method (NBWM) is used to evaluate the weights of risk factors and determine their importance. Secondly, the neutrosophic Weight Aggregated Sum Product Assessments (NWASPAS) method is utilized to calculate the Risk Priority Number (RPN) of the failure modes. The proposed model improves the shortcomings of traditional FMEA and improves the practical applicability and effectiveness of the Best Worst method (BWM) and Weight Aggregated Sum Product Assessments (WASPAS) methods. In addition, this study uses neutrosophic logic to reflect the true judgments of experts in the assessment, which considers authenticity, deviation, and uncertainty to obtain more reliable information. Finally, an empirical case study from an SMPS company headquartered in Taiwan demonstrates the effectiveness and robustness of the proposed model. In addition, by comparing with two other FMEA models, the results show that the proposed model can more clearly reflect the true and effective risks in the assessment. The results can effectively help power supply manufacturers to assess risk factors and determine key failure modes. Full article

(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis)

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23 pages, 9017 KiB

Open AccessArticle

Improving Food Supply Chain Management by a Sustainable Approach to Supplier Evaluation

by Marina Segura, Concepción Maroto, Baldomero Segura and José Carlos Casas-Rosal

Mathematics 2020, 8(11), 1952; https://doi.org/10.3390/math8111952 - 04 Nov 2020

Cited by 16 | Viewed by 3556

Abstract

Increasing food supply chain sustainability means having to deal with many conflicting aspects and involves producers, several departments in distribution companies, and consumers. The objectives of this research are to develop models to solve real-world supplier evaluation problems and validate them with real data on fresh fruits in a supermarket chain. Literature review and results from a survey with managers from purchasing, logistics, and quality departments of a food distribution company are used to establish criteria, to first model the assessment of products and, second, to model supplier evaluation. A multicriteria hybrid approach is proposed, using multi-attribute utility theory (MAUT) to assess the quality of products and Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) to complete their evaluation with strategic criteria to be included in the second phase. The results allow companies to rank suppliers by product and classify them according to the main criteria categories, such as product strategy, food safety, economic, logistic, commercial, green image and corporate social responsibility. A sorting approach is also applied to obtain ordered groups of suppliers. Finally, the models proposed can form the core of a decision support system in order to create and monitor the supplier base in food distribution companies, as well as to inform sustainable decision making. Full article

(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis)

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26 pages, 994 KiB

Open AccessArticle

A Multi-Criteria Pen for Drawing Fair Districts: When Democratic and Demographic Fairness Matter

by Eduardo Álvarez-Miranda, Camilo Campos-Valdés, Maurcio Morales Quiroga, Matías Moreno-Faguett and Jordi Pereira

Mathematics 2020, 8(9), 1404; https://doi.org/10.3390/math8091404 - 21 Aug 2020

Cited by 1 | Viewed by 3210

Abstract

Electoral systems are modified by individuals who have incentives to bias the rules for their political advantage (i.e., gerrymandering). To prevent gerrymandering, legislative institutions can rely on mathematical tools to guarantee democratic fairness and territorial contiguity. These tools have been successfully used in the past; however, there is a need to accommodate additional meanings of the term fairness within the electoral systems of modern democracies. In this paper, we present an optimization framework that considers multiple criteria for drawing districts and assigning the number of representatives. Besides some typical districting criteria (malapportionment and contiguity), we introduce novel criteria for ensuring territorial equilibrium and incentives for candidates to deploy their representation efforts fairly during their campaign and period in office. We test the method, which we denote as Multi-criteria Pen, in a recent and a forthcoming reform of the Chilean electoral system. The results show the potential of our tool to improve the current territorial design and offers insights on the motivations, objectives, and deficiencies of both reform plans. Full article

(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis)

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21 pages, 2676 KiB

Open AccessArticle

A Multi-Criteria Reference Point Based Approach for Assessing Regional Innovation Performance in Spain

by Ana Garcia-Bernabeu, José Manuel Cabello and Francisco Ruiz

Mathematics 2020, 8(5), 797; https://doi.org/10.3390/math8050797 - 14 May 2020

Cited by 17 | Viewed by 2342

Abstract

The evaluation of regional innovation performance through composite innovation indices can serve as a valuable tool for policy-making. While discussion on the best methodology to construct composite innovation indices continues, we are interested in deepening the use of reference levels and the aggregation issue. So far, additive aggregation methods are, largely, the most widespread aggregation rule, thus allowing for full compensability among single indicators. In this paper, we present an integrated assessment methodology to evaluate regional innovation performance using the Multi-Reference Point based Weak and Strong Composite Indicator (MRP-WSCI) approach, which allows defining reference levels and different degrees of compensability. As an example of application to the Regional Innovation Scoreboard, the proposed technique is developed to measure the innovation performance of Spain’s regions taking into account Spanish and European reference levels. The main features of the proposed approach are: (i) absolute or relative reference levels could be previously defined by the decision maker; (ii) by establishing the reference levels, the resulting composite innovation index is an easy-to-interpret measure; and (iii) the non-compensatory strong composite indicator provides an additional layer of information for policy-making (iv) a visualization tool called Light-Diagram is proposed to track the specific strengths and weaknesses of the regions’ innovation performance. Full article

(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis)

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23 pages, 2535 KiB

Open AccessArticle

Fuzzy Multicriteria Models for Decision Making in Gamification

by María Carmen Carnero

Mathematics 2020, 8(5), 682; https://doi.org/10.3390/math8050682 - 01 May 2020

Cited by 12 | Viewed by 2871

Abstract

Gamification is an innovative teaching technique that may prove hugely beneficial when properly used. For this reason, since 2002, the number of situations in which gamification is used has increased exponentially. This large number of options makes it difficult to choose the best application, especially in circumstances where there is the usual uncertainty that real-life decision making involves. To address this problem, this study creates two models, one using a fuzzy analytic hierarchy process (AHP), and the other, which combines fuzzy AHP with the measuring attractiveness by a categorical-based evaluation technique (MACBETH) approach, to choose the best gamification application for the ‘Operations Management’ course, within the Masters in Industrial Engineering. This is the first contribution in the literature combining fuzzy AHP and MACBETH. The decision centre used was the lecturer who teaches the course. There is no precedent in the literature using fuzzy logic to choose the best gamification application for a course. The results of the study show that Socrative is the best gamification application for this course within the Masters, and, as the models begin to be used in degree courses, the better choice would be Quizizz, the more clearly the earlier the course is taught within the degree programme. Full article

(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis)

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21 pages, 6220 KiB

Open AccessArticle

An AHPSort II Based Analysis of the Inequality Reduction within European Union

by Álvaro Labella, Juan Carlos Rodríguez-Cohard, José Domingo Sánchez-Martínez and Luis Martínez

Mathematics 2020, 8(4), 646; https://doi.org/10.3390/math8040646 - 22 Apr 2020

Cited by 16 | Viewed by 2339

Abstract

Nowadays, sustainability is an omnipresent concept in our society, which encompasses several challenges related to poverty, inequality, climate change and so on. The United Nations adopted the Agenda 2030, a plan of action formed of universal Sustainable Developments Goals (SDGs) and targets, which countries have to face in order to shift the world toward a sustainable future. One of the most relevant SDGs since the onset of the financial crisis in 2007 has been the so-called reduced inequalities, which consists of dealing with the inequality of opportunities and wealth between and within countries. However, reducing inequalities depends on many heterogeneous aspects, making it difficult to make a proper analysis that evaluates the European Union (EU) countries performance of this goal. In this study, we introduce a novel approach to evaluate the inequalities in EU countries based on a sorting a multi-criteria decision-making method called AHPSort II. This approach allows to obtain a classification of the EU countries according to their achievements in reducing inequalities to subsequently carry out a deep performance analysis with the aim of drawing conclusions as to the evolution of inequality in them along the years. The results are consistent with the main international organizations’ reports and academic literature, as shown in the Discussion Section. Full article

(This article belongs to the Special Issue Recent Advances and Applications in Multi-Criteria Decision Analysis)

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