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Journal articles on the topic 'Multi Criteria Decision Making'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 January 2025

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1

S.PUSHPARANI, S. PUSHPARANI, and Dr S. SENTHAMILKUMAR Dr.S.SENTHAMILKUMAR. "Selection of Contractor Using Multi-Criteria Decision Making Tools." Indian Journal of Applied Research 4, no. 4 (October 1, 2011): 139–42. http://dx.doi.org/10.15373/2249555x/apr2014/259.

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Kusumadewi, Sri, and Idham Guswaludin. "Fuzzy Multi-Criteria Decision Making." Media Informatika 3, no. 1 (June 7, 2005): 25–38. http://dx.doi.org/10.20885/informatika.vol3.iss1.art3.

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3

Grierson, Donald E. "Pareto multi-criteria decision making." Advanced Engineering Informatics 22, no. 3 (July 2008): 371–84. http://dx.doi.org/10.1016/j.aei.2008.03.001.

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4

Kornbluth, J. S. H. "Dynamic multi-criteria decision making." Journal of Multi-Criteria Decision Analysis 1, no. 2 (October 1992): 81–92. http://dx.doi.org/10.1002/mcda.4020010204.

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5

Abdulla, Mohammed Shahid. "Multi-criteria decision making with overlapping criteria." IIMB Management Review 24, no. 3 (September 2012): 137–42. http://dx.doi.org/10.1016/j.iimb.2012.06.002.

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Abdulla, Mohammed Shahid. "Multi-criteria decision making with overlapping criteria." IIMB Management Review 24, no. 3 (September 2012): 120. http://dx.doi.org/10.1016/j.iimb.2012.07.013.

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7

Azadfallah, Mohammad. "Multi-Criteria Decision Making for Ranking Decision Making Units." International Journal of Productivity Management and Assessment Technologies 6, no. 1 (January 2018): 17–36. http://dx.doi.org/10.4018/ijpmat.2018010102.

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There is no doubt the Data Envelopment Analysis (DEA) is a powerful method for the efficiency evaluation of Decision Making Units (DMUs) with multiple inputs and outputs. Despite its usefulness, DEA has some notable limitations. A significant drawback with this approach is that inability to fully rank the DMUs. In the extant literature, different methods for this purpose have been suggested. While, in the traditional method the first step for the DEA approach is used, and results of this step are input for the DEA ranking method in the second step. To reduce the computational complexity of the traditional method, a new Multiple Criteria Decision Making (MCDM) approach is proposed in this article. In the proposed approaches, one step can achieve full ranking for all DMUs. The results show that although out of 20 DMUs are first in the final ranking ordered by the DEA, the author proposed methods can consider full ranking. Agreement of the proposed methods with the existing approaches are measured by the Spearman's rank correlation coefficient technique. The findings of this study reveal that TOPSIS, Neo-TOPSIS, and AHP ranking results are consistent with the DEA ranking method. Therefore, these proposed methods appear as the possible alternatives to the DEA and DEA ranking models.

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Jaini, Nor I., and Sergei V. Utyuzhnikov. "Critical Criterion Analysis for Multi-criteria Decision Making." International Journal of Applied Physics and Mathematics 6, no. 3 (2016): 129–37. http://dx.doi.org/10.17706/ijapm.2016.6.3.129-137.

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9

Intani, Dini. "Multi Criteria Decision Making for Integrated Assessment of Indonesian Water Company." Journal of Advanced Research in Dynamical and Control Systems 12, SP7 (July 25, 2020): 1050–60. http://dx.doi.org/10.5373/jardcs/v12sp7/20202202.

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YU, Xiaohan, Zeshui XU, and Shousheng LIU. "SYSTEMATIC DECISION MAKING: A EXTENDED MULTI-CRITERIA DECISION MAKING MODEL." Technological and Economic Development of Economy 23, no. 1 (January 22, 2017): 157–77. http://dx.doi.org/10.3846/20294913.2016.1212121.

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Considering some complex multi-criteria decision making (MCDM) problems, in which decision environment is dynamic, there are various interdependences among criteria, and plans (systematized alternatives) consisting of multiple time sequential interdependent actions, cannot be well handled by means of the existing MCDM methods, therefore, we develop a systematic decision making (SDM) as an improvement and supplement of the classic MCDM in this paper. The SDM is for prescribing methods of evaluating and selecting the most favourite plan (a system) from a group of feasible ones concerning influences of time-varying criteria system under dynamic external environment. Through detailed analysis, we separate a SDM problem into multi-period MCDM subproblems, and then a plan can be a combination of time sequential strategies in which each strategy (a subset of actions) is a feasible decision choice of corresponding MCDM sub-problem. After clarifying variety of interdependences, interactions and interrelationships in the SDM problems, such as criteria-interdependences, action-interdependences, interactions between criteria and criteria system, interactions between actions and strategies, interactions between strategies and plans, interactions between internal environment (criteria system) and external environment, feedbacks from external environment to the corresponding MCDM sub-problems, and interrelationships among MCDM sub-problems and so on, we transform the SDM into multi-period interrelated MCDM model which can be dealt with more easily by using multiple optimization models. At the end of the paper, three typical properties of the SDM are proposed and most of the existing MCDM models are pointed out as special cases of the SDM.

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Mary, S. A. Sahaaya Arul, and G. Suganya. "Multi-Criteria Decision Making Using ELECTRE." Circuits and Systems 07, no. 06 (2016): 1008–20. http://dx.doi.org/10.4236/cs.2016.76085.

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12

Brugha, C. M. "Structure of multi-criteria decision-making." Journal of the Operational Research Society 55, no. 11 (November 2004): 1156–68. http://dx.doi.org/10.1057/palgrave.jors.2601777.

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13

Yager, Ronald R. "Categorization in multi-criteria decision making." Information Sciences 460-461 (September 2018): 416–23. http://dx.doi.org/10.1016/j.ins.2017.08.011.

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Dalalah, Doraid, Mohammad Al-Tahat, and Khaled Bataineh. "Mutually Dependent Multi-criteria Decision Making." Fuzzy Information and Engineering 4, no. 2 (June 2012): 195–216. http://dx.doi.org/10.1007/s12543-012-0111-3.

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Šaša Bastinos, Ana, and Marjan Krisper. "Multi-criteria decision making in ontologies." Information Sciences 222 (February 2013): 593–610. http://dx.doi.org/10.1016/j.ins.2012.07.055.

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16

Badarovska Mishevska, Marina. "MULTI CRITERIA DECISION MAKING – RANKING AND PROMOTING EMPLOYEES." KNOWLEDGE INTERNATIONAL JOURNAL 31, no. 5 (June 5, 2019): 1235–41. http://dx.doi.org/10.35120/kij31051235b.

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The analytic hierarchy process (AHP) is a structured technique for organizing and analyzing complex decisions, based on mathematics and psychology. The method was developed by Thomas L. Saaty in the 1970s and has been extensively studied and refined since then. It has particular application in group decision making and is used around the world in a wide variety of decision situation. Rather than prescribing a "correct" decision, the AHP helps decision makers choose one that best suits their goal and their understanding of the problem. The technique provides a comprehensive and rational framework for structuring a decision problem, for representing and quantifying its elements, for relating those elements to overall goals, and for evaluating alternative solutions. Decision making is the choice of one alternative, from two or more, to which the course of the activity is directed and the problem is solved. The decision-making process is a rational attempt by the manager to achieve the goals of the organizational unit. The decision-making process can be thought of as a "brain and nervous system" of an enterprise. Decisions are made when a person wants things to be different in the future. Given each specific situation, making the right decisions is probably one of the most difficult challenges for managers. Managers in day-to-day work deliver programmed and unprogrammed decisions that solve simple or complex problems. Simple decisions have an impact on the short-term performance of the enterprise, and complex decisions have an impact on the long-term future and success of the enterprise. Users of the AHP first decompose their decision problem into a hierarchy of more easily comprehended sub-problems, each of which can be analyzed independently. Once the hierarchy is built, the decision makers systematically evaluate its various elements by comparing them to each other two at a time, with respect to their impact on an element above them in the hierarchy. The AHP converts these evaluations to numerical values that can be processed and compared over the entire range of the problem. In this article, it is explained the application of the AHP method in order to evaluate and promote employees in the enterprise "X" with several criteria. The obtained results enable the manager to evaluate the employees in an objective way and make an objective decision for their promotion. Its application for selecting the best among employees, in their assessment and promotion, allows managers to use a specific and mathematical tool to support the decision. This tool not only supports and qualifies decisions, it also allows managers to justify their choice, as well as to simulate possible results.

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Hu, Eric, Linda Zou, and Craig Langston. "A New Interlink Decision Making Index for Making Multi-criteria Decision." Construction Economics and Building 4, no. 2 (November 18, 2012): 33–42. http://dx.doi.org/10.5130/ajceb.v4i2.2929.

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Multi-criteria decisions usually require measurement or evaluation of performance in different units and their mix by application of weighting factors. This approach lads to potential manipulation of the results as a direct consequence of the applied weightings. In this paper a mechanism that is the brain child of the authors, has been proposed to overcome this problem. It is known as the Interlink Decision Making Index (IDMI) and has all the desired features: simple, interlink (all criteria) and automatically guaranteed dominant influence of critical criteria (i.e. no human weighting needed). The IDMI is capable of reflecting the total merits of a particular option once the normal decision making criteria and (up to two) critical criteria have been chosen. Then, without arbitrarily weighting criteria, comparison and selection of the best possible option can be made. Simple software has been developed to do this numerical transfer and graphic presentation. Two hypothetical examples are presented in the paper to demonstrate the application of the IDMI concept and its advantages over the traditional "tabular and weightingmethod" in the decision making process.

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18

Yager, Ronald R. "Non-numeric multi-criteria multi-person decision making." Group Decision and Negotiation 2, no. 1 (March 1993): 81–93. http://dx.doi.org/10.1007/bf01384404.

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19

Juneja, Abhinav. "Improvising Green Computing Using Multi-Criterion Decision Making." Journal of Advanced Research in Dynamical and Control Systems 12, SP3 (February 28, 2020): 1161–65. http://dx.doi.org/10.5373/jardcs/v12sp3/20201362.

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20

Jayady, Arman, Tonny Hidayat, Erni Qomariyah, BB Suriyani, Muh Najib Husain, Aspizain Caniago, Ana Rusmardiana, et al. "Decision Support System with Multi Criteria Decision Making Technique." Journal of Physics: Conference Series 1933, no. 1 (June 1, 2021): 012017. http://dx.doi.org/10.1088/1742-6596/1933/1/012017.

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21

Suchkova, E. A. "Multi-Criteria Optimization for Decision-Making Support." Bulletin of Kalashnikov ISTU 19, no. 3 (October 10, 2016): 61. http://dx.doi.org/10.22213/2413-1172-2016-3-61-62.

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22

Chen, Chun-An. "Construct a Multi Criteria Decision Making Tool." International Journal of Decision Support System Technology 7, no. 4 (October 2015): 36–50. http://dx.doi.org/10.4018/ijdsst.2015100103.

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When dealing with multi-criteria decision-making problems in both engineering and management research fields, DEMATEL is one of the common methods applied by the researchers. However, so far there is no any easy-to-use DEMATEL application software. Moreover, for DEMATEL, the threshold value setup may vary in different researchers. Later MMDE method was developed, which could obtain clear threshold value. However, its concept and complicated computing process hinder the common researchers to use it quickly. Without any related application software either, it is quite inconvenient to the researchers. Therefore, the study develops an application software that combines with these two methods and incorporates with friendly interfaces. In the paper, it takes how to develop Taiwan into a passenger transport center of East Asia as an example, to illustrate the operation and application of the software. It provides the researchers using DEMATEL and MMDE methods with an excellent and easy-to-good tool.

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23

Azhar, Nayli Adriana, Nurul Asyikin Mohamed Radzi, and Wan Siti Halimatul Munirah Wan Ahmad. "Multi-criteria Decision Making: A Systematic Review." (Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 14, no. 8 (December 23, 2021): 779–801. http://dx.doi.org/10.2174/2352096514666211029112443.

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Multi Criteria Decision Making (MCDM) helps decision makers (DMs) solve highly complex problems. Accordingly, MCDM has been widely used by DMs from various fields as an effective and reliable tool for solving various problems, such as in site and supplier selection, ranking and assessment. This work presents an in-depth survey of past and recent MCDM techniques cited in the literature. These techniques are mainly categorised into pairwise comparison, outranking and distance-based approaches. Some well-known MCDM methods include the Analytical Hierarchy Process (AHP), Analytical Network Process (ANP), Elimination et Choix Traduisant la Realité (ELECTRE), Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Each of these methods is unique and has been used in a vast field of interest to support DMs in solving complex problems. For a complete survey, discussions related to previous issues and challenges and the current implementation of MCDM are also presented.

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24

Gyarmati, József. "Military Application of Multi-Criteria Decision Making." Academic and Applied Research in Military and Public Management Science 14, no. 4 (December 31, 2015): 291–97. http://dx.doi.org/10.32565/aarms.2015.4.3.

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Which is the most appropriate military device for the army based on user interest? This is a frequently asked question. In this paper I will show two methods that can help to select the best one based on the Decision Maker or the user interest and point of view.

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25

Ozcalici, Mehmet. "Allocation with multi criteria decision making techniques." Decision Making: Applications in Management and Engineering 5, no. 2 (October 15, 2022): 78–119. http://dx.doi.org/10.31181/dmame0305102022o.

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26

Mohammadpour, M., S. Zolfaghari, and M. Jabal Ameli. "Hierarchical alternatives in Multi Criteria Decision Making." International Journal of Management and Decision Making 9, no. 4 (2008): 366. http://dx.doi.org/10.1504/ijmdm.2008.019361.

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27

Asadabadi, Mehdi Rajabi. "The stratified multi-criteria decision-making method." Knowledge-Based Systems 162 (December 2018): 115–23. http://dx.doi.org/10.1016/j.knosys.2018.07.002.

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28

Triantaphyllou, Evangelos, and Gerald W. Evans. "Multi-criteria decision making in industrial engineering." Computers & Industrial Engineering 37, no. 3 (November 1999): 505–6. http://dx.doi.org/10.1016/s0360-8352(00)00018-8.

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29

Reuter-Oppermann, Melanie, Sebastian Rachuba, and Andrea Raith. "Multi-criteria decision making in health care." Operations Research for Health Care 23 (December 2019): 100234. http://dx.doi.org/10.1016/j.orhc.2019.100234.

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30

Rezaei, Jafar. "Best-worst multi-criteria decision-making method." Omega 53 (June 2015): 49–57. http://dx.doi.org/10.1016/j.omega.2014.11.009.

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31

Yager, Ronald R., and Naif Alajlan. "Fuzzy Measures in Multi-Criteria Decision Making." Procedia Computer Science 62 (2015): 107–15. http://dx.doi.org/10.1016/j.procs.2015.08.421.

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32

Ogryczak, Włodzimierz, and Rudolf Vetschera. "Methodological foundations of multi-criteria decision making." European Journal of Operational Research 158, no. 2 (October 2004): 267–70. http://dx.doi.org/10.1016/j.ejor.2003.06.003.

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33

Sridhar, Prasanna, Asad Madni, and Mo Jamshidi. "Multi-Criteria Decision Making in Sensor Networks." IEEE Instrumentation & Measurement Magazine 11, no. 1 (2008): 24–29. http://dx.doi.org/10.1109/im-m.2008.4449011.

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34

Kostner, Daniel. "Multi-criteria decision making via multivariate quantiles." Mathematical Methods of Operations Research 91, no. 1 (August 2, 2019): 73–88. http://dx.doi.org/10.1007/s00186-019-00675-9.

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35

Greenstein, Gil. "Paradox of Multi Criteria Decision Making Processes." Universal Journal of Management 5, no. 8 (August 2017): 395–403. http://dx.doi.org/10.13189/ujm.2017.050804.

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36

Kharal, Athar. "A Neutrosophic Multi-Criteria Decision Making Method." New Mathematics and Natural Computation 10, no. 02 (June 3, 2014): 143–62. http://dx.doi.org/10.1142/s1793005714500070.

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This work presents a method of multi-criteria decision making (MCDM) using neutrosophic sets. Besides studying some interesting mathematical properties of the method, algorithm viz neut-MCDM is presented. The work also furnishes the fundamentals of neutrosophic set theory succinctly, to provide a first introduction of neutrosophic sets for the MCDM community. To illustrate the computational details, neut-MCDM has been applied to the problem of university faculty selection against a given set of criteria.

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37

Agrell, Per J. "On redundancy in multi criteria decision making." European Journal of Operational Research 98, no. 3 (May 1997): 571–86. http://dx.doi.org/10.1016/0377-2217(95)00340-1.

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38

Ray, Pradip K., and S. Sahu. "Productivity measurement through multi-criteria decision making." Engineering Costs and Production Economics 20, no. 2 (October 1990): 151–63. http://dx.doi.org/10.1016/0167-188x(90)90099-4.

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39

Vasconcelos, Ana G. G., Renan M. V. Rodrigues Almeida, and Flávio F. Nobre. "Path Analysis and Multi-Criteria Decision Making." Annals of Epidemiology 11, no. 6 (August 2001): 377–84. http://dx.doi.org/10.1016/s1047-2797(01)00232-0.

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40

Chechnev, V. B. "Analysis and classification of multi-criteria decision-making methods." Ontology of designing 14, no. 4 (November 7, 2024): 607–24. http://dx.doi.org/10.18287/2223-9537-2024-14-4-607-624.

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Decision-making requires in-depth analysis through the evaluation and comparison of various alternative solutions. These tasks are characterized by multiple criteria used for comparison. The variability of parameters and conditions in decision-making has led to the development of numerous methods aimed at facilitating this process effectively. Currently, several hundred multi-criteria decision-making methods are known, making it challenging to select the most appropriate one for practical use. Therefore, research on the analysis, classification, and systematization of multi-criteria decision-making methods is relevant and essential for decision-makers and developers of decision support systems. Most classifications emphasize the methodologies and purposes of these methods, often overlooking their inherent limitations. This article attempts to systematize the main multi-criteria decision-making methods, considering their limitations. It analyzes the most widely used methods and their classifications. Based on identified limitations, the paper proposes a classification of multi-criteria decision-making methods and guidelines for selecting them. Applying this approach can enhance the validity of method selection and, consequently, the effectiveness of the decisions made.

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Saaty, Thomas L., and Daji Ergu. "When is a Decision-Making Method Trustworthy? Criteria for Evaluating Multi-Criteria Decision-Making Methods." International Journal of Information Technology & Decision Making 14, no. 06 (November 2015): 1171–87. http://dx.doi.org/10.1142/s021962201550025x.

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Decision makers often face complicated decision problems with intangible and conflicting criteria. Numerous multi-criteria decision-making (MCDM) methods have been proposed to handle the measurement of the priorities of conflicting tangible/intangible criteria and in turn use them to choose the best alternative for a decision. However, the presence of many MCDM methods bewilders users. The existence of these methods becomes a decision problem in itself, and decision makers may be uncertain about which one to use. Thus the comparative analysis and evaluation of various MCDM methods has come under scrutiny by both researchers and practitioners in order to discover if there are logical, mathematical, social or practical reasons why one method is better than another. Criteria for their evaluation are the first important issue that needs to be resolved. In this paper, 16 criteria are introduced that may be used to judge and evaluate various MCDM methods. The criteria proposed and some guidelines for their evaluation are given to help readers evaluate these MCDM methods.

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42

Dos Santos, Francisco J., and André L. V. Coelho. "A multi-view approach to multi-criteria decision making." International Journal of Information and Decision Sciences 15, no. 1 (2023): 1. http://dx.doi.org/10.1504/ijids.2023.10054770.

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d, Francisco J., os Santos, and André L. V. Coelho. "A multi-view approach to multi-criteria decision making." International Journal of Information and Decision Sciences 15, no. 1 (2023): 1. http://dx.doi.org/10.1504/ijids.2023.129655.

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44

I, Ketut Santra, Wayan Sukarta I, and Ni Wayan Sumetri. "Multi Criteria-based Decision Making of Affiliative Orchestration Capability of Balinese Tourism Management." Webology 19, no. 1 (January 20, 2022): 5444–54. http://dx.doi.org/10.14704/web/v19i1/web19365.

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The study analyzes what tasks are carried out and how the tourism village manager harmonizes the differences in interests between stakeholders in the tourist village. This research was conducted by examining the practice of governance competencies carried out by tourism village managers in Bali by conceptualizing Affiliative Orchestration Capability (AOC). By using multiple criteria of stakeholders as the basis for decision making, this study formulates a set of competency models for tourism village managers. The results underline the importance of affiliative orchestration ability as a set of competencies for tourism village managers who are able to harmonize all stakeholder interests in Bali. Stakeholder decision making shows that tourism village managers who practice affiliative orchestration skills tend to be better able to manage tourist villages that meet the criteria for sustainable tourism villages.

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45

El Hachami, Khadija, Youssef Lamrani Alaoui, and Mohamed Tkiouat. "Sectorial evaluation of Islamic banking contracts: a fuzzy multi-criteria-decision-making approach." Investment Management and Financial Innovations 16, no. 2 (July 5, 2019): 370–82. http://dx.doi.org/10.21511/imfi.16(2).2019.31.

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Improving the efficiency and performance of microfinance investments is essential to achieve its objectives in terms of economic and social development. One parameter that influences such a performance is the kind of the activity exercised by the micro-entrepreneurs. The aim of this paper is to provide a decision-making guide to help both microfinance institutions and investors to choose the appropriate Islamic banking contract with respect to each sector of activity. To attain this goal, an Intuitionistic Fuzzy TOPSIS evaluation is conducted in collaboration with Moroccan Islamic finance experts and practitioners. The proposed approach has the advantage to deal with the lack of quantitative historical data, as well as the uncertainty of the decision makers’ judgments. The suggested work will be helpful for the Moroccan participative banks and for the future Islamic microfinance institutions as well.

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46

Osintsev, Nikita Anatolyevich. "Multi-criteria decision-making in transport and logistics." Transport of the Urals, no. 4 (2021): 3–17. http://dx.doi.org/10.20291/1815-9400-2021-4-3-17.

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In the last decade, in transport and logistics, the scientific and practical direction for the development and improvement of methods for multi-criteria decision-making (MCDM) has been actively developing. The paper provides an overview of research in the field of using MCDM, shows the features and different approaches to the classification of MCDM, the practice of their use in transport and in logistics activities, an approach to systematizing the methods is proposed. An MCDM model and a calculated example of ranking management decisions to improve transport and logistics activities at an enterprise using 11 MCDM methods are presented. The FUCOM method is used to determine the weight of the criteria. The ranking of management decisions is performed by comparing 10 methods: SAW, TOPSIS, PROMETHEE, COPRAS, MOORA, WASPAS, MAIRCA, EDAS, MABAC and MARCOS.

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47

Unal, Okan, and Erfan Maleki. "Shot peening optimization with complex decision-making tool: Multi criteria decision-making." Measurement 125 (September 2018): 133–41. http://dx.doi.org/10.1016/j.measurement.2018.04.077.

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48

HRYNCHAK, N. "Conceptual aspects of multi-criteria decision-making in management activity." Scientific Bulletin of the National Academy of Statistics, Accounting and Audit, no. 1-2 (March 31, 2023): 68–76. http://dx.doi.org/10.31767/nasoa.1-2-2023.07.

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The activities of enterprises in conditions of instability of the external environment, high rates of technical progress and processes of globalization create many complex problems for them, the solution of which requires the adoption of balanced and effective management decisions. Decision-making is one of the most important elements of managing the development of an enterprise, both in the short-term and in the long-term. In this regard, there is an intensive development of various tools and methods of the management decision-making process. The conceptual aspects of multi-criteria decision-making are considered in the article. The essence of the multi-criteria decision-making method was determined, the scope of its application was investigated. It is substantiated that in the process of multi-criteria decision-making, a significant number of criteria are considered, however, to make an optimal decision, all alternatives must have common criteria that directly affect the solution of a specific problem and lead to the adoption of a better decision. The methods of multi-criteria decision-making are distinguished and characterized. It was determined that considering the rapid, dynamic, sometimes chaotic development of the external business environment, in which effective management decision-making will be based on considering an increasing number of various factors, the specifics of the practical application of various methods of multi-criteria decision-making require further research.

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49

Zizovic, Miodrag, Nada Damljanovic, and Malisa Zizovic. "Multi-criteria decision making method for models with the dominant criterion." Filomat 31, no. 10 (2017): 2981–89. http://dx.doi.org/10.2298/fil1710981z.

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Abstract:

In all practical problems associated with the selection and assessment, almost always criteria have different importance. The priorities of criteria are expressed by weighted coefficients. Every decision maker has to establish criteria priority scale. This can be done directly - degrees of criteria importance defined by judgment of experts, or indirectly - degrees of criteria importance calculated by alternatives themselves. Many multi-criteria decision methods allow some kind of compensatory between criteria. The low performance on an important criterion can be redeemed in overall aggregation by good performance on few other less important criteria. In this paper, we present the method which provides that such an important piece of information must be preserved: If an alternative does not satisfy a dominant criterion, then its overall aggregation value is zero.

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Więckowski, Jakub, and Wojciech Sałabun. "Supporting multi-criteria decision-making processes with unknown criteria weights." Engineering Applications of Artificial Intelligence 140 (January 2025): 109699. http://dx.doi.org/10.1016/j.engappai.2024.109699.

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