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Journal articles on the topic 'Multicriteria decision making'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Hendriks, Margriet M. W. B., Jan H. de Boer, Age K. Smilde, and Durk A. Doornbos. "Multicriteria decision making." Chemometrics and Intelligent Laboratory Systems 16, no. 3 (1992): 175–91. http://dx.doi.org/10.1016/0169-7439(92)80036-4.

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2

Yager, R. R. "Modeling Prioritized Multicriteria Decision Making." IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 34, no. 6 (2004): 2396–404. http://dx.doi.org/10.1109/tsmcb.2004.837348.

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3

Novikova, Natalia M., and Irina I. Pospelova. "Multicriteria decision making under uncertainty." Mathematical Programming 92, no. 3 (2002): 537–54. http://dx.doi.org/10.1007/s101070100289.

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4

Hum Tchemra, Angela. "Adaptivity in Multicriteria Decision Making." IEEE Latin America Transactions 9, no. 2 (2011): 160–70. http://dx.doi.org/10.1109/tla.2011.5765569.

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5

Kumar, Kamesh, and M. K. Sharma. "Generalized Fuzzy Technique and its Consistent Assessment in Multicriteria Decision Making of Medical Decisions." Indian Journal Of Science And Technology 17, no. 42 (2024): 4438–48. http://dx.doi.org/10.17485/ijst/v17i42.3115.

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Objectives: The purpose of this study is to develop a decision-making expert system to assist the diagnostic decisions effectively. Generalized fuzzy sets (Vague sets) are used to model the uncertainty that exists in the process. Method: Initially, concepts of centroid and signed distance are generalized for Trapezoidal Vague Numbers (TVNs). This model introduces some desirable properties for the proposed distance measure. A multicriteria decision-making (MCDM) is introduced using trapezoidal vague numbers (TVNs) and other intuitions in medical diagnostics. In this MCDM, firstly, each symptom

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6

Hao, Qinxia, Shah Nazir, Xiaoxu Gao, Li Ma, and Muhammad Ilyas. "A Review on Multicriteria Decision Support System and Industrial Internet of Things for Source Code Transformation." Scientific Programming 2021 (January 13, 2021): 1–9. http://dx.doi.org/10.1155/2021/6661272.

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The large scale increase of communication and number of devices in the Industrial Internet of Things (IIoT) has rapidly enabled practitioners to make decisions based on multicriteria. Multicriteria decision support systems (MCDSSs) play an important role in decision-making for a particular situation based on several criteria. Making of decision based on multicriteria is the main issues for research community and practitioners of the IIoT. Several decision support systems (DSSs) are offered for making decisions which have the potentiality to support the activities of the decision-making process

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7

Voronin, Albert, and Alina Savchenko. "Compromise and Consensus in Multicriteria Decision-Making." Information Theories and Applications 28, no. 4 (2021): 336–50. http://dx.doi.org/10.54521/ijita28-04-p02.

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Various approaches to solving multicriteria problems are considered, depending on the role of constraints in the problem statement. If the constraints are fixed and specified, then the calculation algorithm includes the preferences of the decision maker, and the corresponding multicriteria problem has a fundamentally compromise solution. If the values of the restrictions can be varied, then it becomes possible to obtain consensus decisions, and the calculation algorithm is free of heuristic elements.

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8

Liang, Liang, Ren Yan Jiang, and Yin Liang. "A Multicriteria Decision Method with Uncertain Information in Financial Credit Loan Decision-Making." Applied Mechanics and Materials 52-54 (March 2011): 1868–72. http://dx.doi.org/10.4028/www.scientific.net/amm.52-54.1868.

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It is difficult to obtain the correct criteria weights with uncertain information in the multicriteria decision-making. Many methods depend on the subjective estimate. Therefore, a method is presented to evaluate the samples ranking only need the importance order of criteria. It evaluates firstly the overall ranking scores of samples based on the graphical classification and multicriteria hierarchical integrated methods. Subsequently, the relation model between the criteria scores and overall ranking scores of samples is built by linear regression. Finally, a fincial credit loan decision-makin

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9

GRABOŚ, RAFAL. "ANSWER SET PROGRAMMING AND COMBINATORIAL MULTICRITERIA DECISION MAKING." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 14, no. 04 (2006): 393–420. http://dx.doi.org/10.1142/s0218488506004096.

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The majority of approaches to multicriteria optimization are based on quantitative representations of preferences of a decision maker, in which numerical procedures of multicriteria analysis are used for aggregation purposes. However, very often qualitative data cannot be known in terms of absolute values so that a qualitative approach is needed. Moreover, the multicriteria methods are directly applicable when alternatives are individuals-then they may be explicitly listed and ordered by an agent. However, sometimes the set of alternatives has combinatorial structure and it must be selected fr

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10

Wibowo, Santoso, and Srimannarayana Grandhi. "Benchmarking knowledge management practices in small and medium enterprises." Benchmarking: An International Journal 24, no. 5 (2017): 1215–33. http://dx.doi.org/10.1108/bij-01-2016-0013.

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Purpose The purpose of this paper is to formulate the process of measuring and benchmarking the performance of knowledge management (KM) practices as a multicriteria group decision-making problem and present a new multicriteria group decision-making approach for effectively evaluating the performance of KM practices to meet the interests of various stakeholders in small and medium enterprises (SMEs). Design/methodology/approach A new multicriteria group decision-making approach is developed for evaluating the performance of KM practices of individual SMEs. Intuitionistic fuzzy numbers are used

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11

Yager, Ronald R. "Multicriteria Decision-Making Using Fuzzy Measures." Cybernetics and Systems 46, no. 3-4 (2015): 150–71. http://dx.doi.org/10.1080/01969722.2015.1012884.

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12

Janssen, Ron, and Marjan Van Herwijnen. "A toolbox for multicriteria decision-making." International Journal of Environmental Technology and Management 6, no. 1/2 (2006): 20. http://dx.doi.org/10.1504/ijetm.2006.008252.

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13

Grabisch, Michel. "Fuzzy integral in multicriteria decision making." Fuzzy Sets and Systems 69, no. 3 (1995): 279–98. http://dx.doi.org/10.1016/0165-0114(94)00174-6.

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14

Keller, H. R., D. L. Massart, and J. P. Brans. "Multicriteria decision making: A case study." Chemometrics and Intelligent Laboratory Systems 11, no. 2 (1991): 175–89. http://dx.doi.org/10.1016/0169-7439(91)80064-w.

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15

Mareschal, Bertrand. "Stochastic multicriteria decision making and uncertainty." European Journal of Operational Research 26, no. 1 (1986): 58–64. http://dx.doi.org/10.1016/0377-2217(86)90159-1.

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16

Cziner, Krisztina, Mari Tuomaala, and Markku Hurme. "Multicriteria decision making in process integration." Journal of Cleaner Production 13, no. 5 (2005): 475–83. http://dx.doi.org/10.1016/j.jclepro.2003.09.003.

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17

Wang, Hsiao-Fan. "Fuzzy multicriteria decision making—an overview." Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology 9, no. 1-2 (2000): 61–83. https://doi.org/10.3233/ifs-2000-119.

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18

Žnidaršič, Vinko, Katarina V. Dojić, and Lazar N. Milić. "Selection of Landing Site for Infantry River Crossing Using Aluminum Boat M70: Application of DIBR and Topsis Method." International conference KNOWLEDGE-BASED ORGANIZATION 30, no. 1 (2024): 1–8. http://dx.doi.org/10.2478/kbo-2024-0027.

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Abstract This research analyzes the problem of choosing a location for conducting infantry river crossing using the aluminum boat M70, applying the multicriteria decision-making method. It has been found that the use of these models significantly accelerates and simplifies the decision-making process, contributing to efficiency and speed in the process itself. At the same time, a comparison was made between the results obtained using multicriteria decision-making methods and the opinions of experts in the field of overcoming water obstacles. The research conclusions emphasize that multicriteri

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19

Limayem, Moez, and Gerardine DeSanctis. "Providing Decisional Guidance for Multicriteria Decision Making in Groups." Information Systems Research 11, no. 4 (2000): 386–401. http://dx.doi.org/10.1287/isre.11.4.386.11874.

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20

Piegat, Andrzej, and Wojciech Sałabun. "Identification of a Multicriteria Decision-Making Model Using the Characteristic Objects Method." Applied Computational Intelligence and Soft Computing 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/536492.

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This paper presents a new, nonlinear, multicriteria, decision-making method: the characteristic objects (COMET). This approach, which can be characterized as a fuzzy reference model, determines a measurement standard for decision-making problems. This model is distinguished by a constant set of specially chosen characteristic objects that are independent of the alternatives. After identifying a multicriteria model, this method can be used to compare any number of decisional objects (alternatives) and select the best one. In the COMET, in contrast to other methods, the rank-reversal phenomenon

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21

Gogodze, Joseph. "Ranking Methods for Multicriteria Decision-Making: Application to Benchmarking of Solvers and Problems." Scientific Programming 2021 (July 11, 2021): 1–14. http://dx.doi.org/10.1155/2021/5513860.

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Evaluating the performance assessments of solvers (e.g., for computation programs), known as the solver benchmarking problem, has become a topic of intense study, and various approaches have been discussed in the literature. Such a variety of approaches exist because a benchmark problem is essentially a multicriteria problem. In particular, the appropriate multicriteria decision-making problem can correspond naturally to each benchmark problem and vice versa. In this study, to solve the solver benchmarking problem, we apply the ranking-theory method recently proposed for solving multicriteria

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22

Martinkutė-Kaulienė, Raimonda, Radvinė Skobaitė, Viktorija Stasytytė, and Nijolė Maknickienė. "Comparison of multicriteria decision-making methods in portfolio formation." Finance, Markets and Valuation 7, no. 2 (2021): 60–72. http://dx.doi.org/10.46503/qwpu4486.

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Investors apply various methods to select stocks and construct an investment portfolio. In the majority of methods, the principle of diversification is relevant. Also, sometimes investors‘ behaviour generate biases related to portfolio formation. Multicriteria decision-making methods can overcome such shortcomings of investors' decision-making; thus, they are widely used for portfolio selection. In the performed research, the portfolio is constructed from the stocks of the Spanish stock market. Stocks are selected based on financial indicators. SAW and TOPSIS multicriteria methods are used to

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23

Mitkus, Sigitas, and Eva Trinkūnienė. "MODELS OF INDICATOR SYSTEMS OF CONSTRUCTION CONTRACTION AGREEMENTS." JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 12, no. 4 (2006): 327–35. http://dx.doi.org/10.3846/13923730.2006.9636410.

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A number of multicriteria decisions must be made during construction investment processes. A number of support systems for multicriteria tasks of construction investment processes are available. A part of them is reviewed in this article. Effectiveness of the construction investment process is greatly influenced by an appropriate formulation of a construction contraction agreement (CCA). In order to formulate the effective contraction agreements, multicriteria techniques for evaluating and comparing CCAs must be created. Besides technical, organisational and economic aspects of construction, l

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24

Mustafa, Saima, Neelofar Safdar, Murrium Bibi, A. F. Sayed, Muhammad Ghaffar Khan, and Zabidin Salleh. "A Study of Bipolar Fuzzy Soft Sets and Its Application in Decision-Making Problems." Mathematical Problems in Engineering 2021 (October 19, 2021): 1–12. http://dx.doi.org/10.1155/2021/5742288.

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We live in a society where we have to deal with so many social issues daily, and making a right choice is everyone’s main concern. This study is based on the selection of right university while getting admission which is the core issue for students nowadays. We are concerned with bipolar fuzzy multicriteria decision-making methods. The main purpose is to provide guidance to the students for determining the best university and evaluating the factors that are affecting while getting admission. We thus combined bipolar fuzzy and soft expert sets to give multicriteria decision-making approach that

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25

Hu, Jianmiao, and Chong Chen. "Exploration of Normal Stochastic Multicriteria Decision-Making and Legal Dilemma in Project Investment." Mathematical Problems in Engineering 2021 (November 19, 2021): 1–10. http://dx.doi.org/10.1155/2021/1082186.

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The purpose is to help enterprise managers make more accurate, scientific, and objective decisions on the optimal supplier in project investment, improve investment return and overall efficiency, and reduce investment risk. Following an introduction of normal stochastic multicriteria decision-making, a normal stochastic multicriteria decision-making method is proposed based on Bayesian Network- (BN-) Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to help investors select suppliers. First, product cost, product quality, and product service are selected as evaluation

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26

Kiker, Gregory A., Todd S. Bridges, Arun Varghese, Thomas P. Seager, and Igor Linkov. "Application of Multicriteria Decision Analysis in Environmental Decision Making." Integrated Environmental Assessment and Management 1, no. 2 (2005): 95. http://dx.doi.org/10.1897/ieam_2004a-015.1.

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27

Wibowo, Santoso, and Hepu Deng. "Consensus-based decision support for multicriteria group decision making." Computers & Industrial Engineering 66, no. 4 (2013): 625–33. http://dx.doi.org/10.1016/j.cie.2013.09.015.

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28

Dubois, D., M. Grabisch, F. Modave, and H. Prade. "Relating decision under uncertainty and multicriteria decision making models." International Journal of Intelligent Systems 15, no. 10 (2000): 967–79. http://dx.doi.org/10.1002/1098-111x(200010)15:10<967::aid-int5>3.0.co;2-d.

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29

Denney, Dennis. "Multicriteria Decision-Making in Strategic Reservoir Planning." Journal of Petroleum Technology 54, no. 09 (2002): 83–84. http://dx.doi.org/10.2118/0902-0083-jpt.

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30

Zavadskas, E., A. Kaklauskas, and Z. Turskis. "MULTICRITERIA DECISION-MAKING SYSTEM FOR BUILDING REFURBISHMENT." Statyba 3, no. 12 (1997): 62–68. http://dx.doi.org/10.1080/13921525.1997.10531368.

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31

Minch, Robert P., and G. Lawrence Sanders. "COMPUTERIZED INFORMATION SYSTEMS SUPPORTING MULTICRITERIA DECISION MAKING." Decision Sciences 17, no. 3 (1986): 395–413. http://dx.doi.org/10.1111/j.1540-5915.1986.tb00233.x.

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32

VillarinhoRosa, Lúcio, and Assed Naked Haddad. "Building Sustainability Assessment throughout Multicriteria Decision Making." Journal of Construction Engineering 2013 (September 30, 2013): 1–9. http://dx.doi.org/10.1155/2013/578671.

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Opinion and choice strongly influence sustainability concepts. The building construction industry, in particular property developers, has been charged with promoting excess environmental impacts ranging from overuse of resources to pollution generation. This paper presents an application of sustainability concepts to building projects, as well as to the development of practices, methodology, and tools for evaluating existing buildings. This study will detail how current systems to evaluate building performance operate and how to improve them. This approach utilizes the analytic hierarchy proce

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33

Bogdanović, Strahinja, and Miroljub Hadžić. "Strategic multicriteria decision-making process in agriculture." Ekonomika poljoprivrede 66, no. 1 (2019): 89–106. http://dx.doi.org/10.5937/ekopolj1901089b.

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34

Aliev, Rafik A., Oleg H. Huseynov, and Rafig R. Aliyev. "Multicriteria dynamic decision making under Z-information." Information Sciences 694 (March 2025): 121703. https://doi.org/10.1016/j.ins.2024.121703.

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35

Rolka, Leszek, Alicja Mieszkowicz-Rolka, and Grzegorz Drupka. "Multicriteria decision-making in flight route selection." Aircraft Engineering and Aerospace Technology 92, no. 9 (2020): 1377–84. http://dx.doi.org/10.1108/aeat-12-2019-0245.

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Purpose This paper aims to present a hybrid logical-arithmetic approach for selecting optimal flight routes. It can be used in the framework of free route airspace (FRA), which is aimed at achieving higher efficiency of air traffic management. Design/methodology/approach At the first stage, an initial subset of flight routes is selected that are promising alternatives with respect to single numerical criteria. At the second stage, a hybrid multicriteria decision model is constructed, consisting of numerical criteria and additional linguistic criteria. At the third stage, the numerical and ling

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36

BOGETOFT, PETER, and JORGEN TIND. "Dual Decomposition Schemes for Multicriteria Decision Making." IMA Journal of Management Mathematics 2, no. 4 (1989): 269–79. http://dx.doi.org/10.1093/imaman/2.4.269.

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37

Peng, Yi, Yong Zhang, Gang Kou, Jun Li, and Yong Shi. "Multicriteria Decision Making Approach for Cluster Validation." Procedia Computer Science 9 (2012): 1283–91. http://dx.doi.org/10.1016/j.procs.2012.04.140.

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38

GRABISCH, Michel, Christophe LABREUCHE, and Mustapha RIDAOUI. "On importance indices in multicriteria decision making." European Journal of Operational Research 277, no. 1 (2019): 269–83. http://dx.doi.org/10.1016/j.ejor.2019.02.035.

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39

Engau, Alexander, and Margaret M. Wiecek. "2D decision-making for multicriteria design optimization." Structural and Multidisciplinary Optimization 34, no. 4 (2006): 301–15. http://dx.doi.org/10.1007/s00158-006-0078-y.

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40

Shukla, Vikas, Guillaume Auriol, and Keith W. Hipel. "Multicriteria Decision-Making Methodology for Systems Engineering." IEEE Systems Journal 10, no. 1 (2016): 4–14. http://dx.doi.org/10.1109/jsyst.2014.2344635.

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41

Kobryń, Andrzej. "Multicriteria Decision Making in Geodetic Network Design." Journal of Surveying Engineering 146, no. 1 (2020): 04019018. http://dx.doi.org/10.1061/(asce)su.1943-5428.0000301.

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42

Potomkin, M. M. "Evaluating the Validity of Multicriteria Decision-Making." Cybernetics and Systems Analysis 54, no. 6 (2018): 930–35. http://dx.doi.org/10.1007/s10559-018-0095-z.

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43

Kahraman, Cengiz, Sezi Cevik Onar, and Basar Oztaysi. "Fuzzy Multicriteria Decision-Making: A Literature Review." International Journal of Computational Intelligence Systems 8, no. 4 (2015): 637–66. http://dx.doi.org/10.1080/18756891.2015.1046325.

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44

Zaychenko, Olena Yu, and Yuriy P. Zaychenko. "Multicriteria decision-making problems under fuzzy conditions." System research and information technologies, no. 4 (November 15, 2016): 79–87. http://dx.doi.org/10.20535/srit.2308-8893.2016.4.08.

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45

San Cristóbal, José Ramón. "Contractor Selection Using Multicriteria Decision-Making Methods." Journal of Construction Engineering and Management 138, no. 6 (2012): 751–58. http://dx.doi.org/10.1061/(asce)co.1943-7862.0000488.

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46

Yager, Ronald R., and Naif Alajlan. "Multicriteria Decision-Making With Imprecise Importance Weights." IEEE Transactions on Fuzzy Systems 22, no. 4 (2014): 882–91. http://dx.doi.org/10.1109/tfuzz.2013.2277734.

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47

Yager, Ronald R. "Pythagorean Membership Grades in Multicriteria Decision Making." IEEE Transactions on Fuzzy Systems 22, no. 4 (2014): 958–65. http://dx.doi.org/10.1109/tfuzz.2013.2278989.

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48

Satyadas, Antony, and H. C. Chen. "Multicriteria multigoal decision making - the fuzzy paradigm." Computers & Industrial Engineering 23, no. 1-4 (1992): 393–96. http://dx.doi.org/10.1016/0360-8352(92)90144-9.

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49

Aggarwal, Manish. "Linguistic Discriminative Aggregation in Multicriteria Decision Making." International Journal of Intelligent Systems 31, no. 6 (2016): 529–55. http://dx.doi.org/10.1002/int.21793.

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50

Aggarwal, Manish. "Soft information set for multicriteria decision making." International Journal of Intelligent Systems 34, no. 12 (2019): 3241–59. http://dx.doi.org/10.1002/int.22192.

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