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Journal articles on the topic 'Multiple criteria decision making'

Author: Grafiati

Published: 4 June 2021

Last updated: 28 July 2024

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1

Huizingh, K. R. E., and H. C. J. Vrolijk. "Multiple Criteria Decision Making." Maandblad Voor Accountancy en Bedrijfseconomie 67, no. 12 (December 1, 1993): 635–46. http://dx.doi.org/10.5117/mab.67.13669.

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2

Hipel, K. W., K. J. Radford, and L. Fang. "Multiple participant-multiple criteria decision making." IEEE Transactions on Systems, Man, and Cybernetics 23, no. 4 (1993): 1184–89. http://dx.doi.org/10.1109/21.247900.

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3

Hülle, Judith, and Ralf Kaspar. "Multiple Criteria Decision Making (MCDM)." Controlling 22, no. 3 (2010): 207–8. http://dx.doi.org/10.15358/0935-0381-2010-3-207.

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4

Voskoglou, Michael Gr. "Grey Multiple-Criteria Decision-Making." International Journal of Grey Systems 4, no. 1 (June 30, 2024): 5–10. http://dx.doi.org/10.52812/ijgs.88.

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Decision Making (DM) is one of the most important components of human cognition. In particular, the Multiple-Criteria DM (MCDM), is a composite form of DM evaluating options with conflicting goals and choosing the best solution among the existing ones. Following the fuzzy DM criterion of Bellman and Zadeh in 1970, several other methods have been developed by other researchers for DM in fuzzy environments. Here we present a parametric, MCDM method utilizing grey numbers as tools. This method improves an earlier approach of Maji and colleagues in 2002, who used the tabular representation of a soft set as a tool for parametric MCDM in a fuzzy environment. The method is also extended to cover cases of weighted DM and suitable examples are presented illustrating our results.

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5

Ben Amor, Sarah, Anissa Frini, and Gilles Reinhardt. "Preface: multiple criteria decision making for sustainable decisions." Annals of Operations Research 293, no. 2 (September 25, 2020): 401–3. http://dx.doi.org/10.1007/s10479-020-03786-3.

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6

Pearman, Alan, and Mario T. Tabucanon. "Multiple Criteria Decision Making in Industry." Journal of the Operational Research Society 41, no. 9 (September 1990): 883. http://dx.doi.org/10.2307/2583506.

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7

Jaâfar, Inès Ben, and Khaled Ghédira. "Coordination based Multiple Criteria Decision Making." Journal of Decision Systems 16, no. 1 (January 2007): 37–56. http://dx.doi.org/10.3166/jds.16.37-56.

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8

Pearman, Alan. "Multiple Criteria Decision Making in Industry." Journal of the Operational Research Society 41, no. 9 (September 1990): 883. http://dx.doi.org/10.1057/jors.1990.128.

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9

WIECEK, M., MATTHIASEHRGOTT, G. FADEL, and J. RUIFIGUEIRA. "Multiple criteria decision making for engineering." Omega 36, no. 3 (June 2008): 337–39. http://dx.doi.org/10.1016/j.omega.2006.10.001.

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10

Mykhalevich, V. M. "Two criteria in multiple decision making." Cybernetics and Systems Analysis 48, no. 2 (March 2012): 217–26. http://dx.doi.org/10.1007/s10559-012-9400-4.

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11

Hsu, Li-Chang. "A HYBRID MULTIPLE CRITERIA DECISION-MAKING MODEL FOR INVESTMENT DECISION MAKING." Journal of Business Economics and Management 15, no. 3 (July 8, 2014): 509–29. http://dx.doi.org/10.3846/16111699.2012.722563.

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Investments are accompanied by risks. How investors choose the right investment tools to assist in the selection of investment targets is a topic worth exploring. Therefore, this study aimed to develop an investment decision-making process to deal with this issue. Firstly, we proposed a globalized modified grey relational analysis to select the representative indicators including the financial indicators and risk measurement indicators. Then we combined financial and risk evaluation indicators, and divided companies into low, moderate and high-risk groups through the grey clustering analysis. Finally, Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) combined with the grey entropy weighting method was applied to business performance evaluation and sorting of each grouping. In order to verify this study, a combination of 21 financial ratios and four risk indicators was utilized in order to verify the evaluation and decision-making process in the operating performance of 62 listed opto-electronics companies in Taiwan. The results of ranking the operating performance for each group can be made available to company managers as a reference in order to enhance competitiveness and business performance. The results can also be used as the basis for decision-making to aid investors who are facing many investment portfolios.

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12

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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13

Carlsson, Christer, and Robert Fullér. "Fuzzy multiple criteria decision making: Recent developments." Fuzzy Sets and Systems 78, no. 2 (March 1996): 139–53. http://dx.doi.org/10.1016/0165-0114(95)00165-4.

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14

Fu, Chao, Kaile Zhou, and Min Xue. "Fair framework for multiple criteria decision making." Computers & Industrial Engineering 124 (October 2018): 379–92. http://dx.doi.org/10.1016/j.cie.2018.07.039.

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15

Kou, Gang, Kaisa Miettinen, and Yong Shi. "Multiple Criteria Decision Making: Challenges and Advancements." Journal of Multi-Criteria Decision Analysis 18, no. 1-2 (January 2011): 1–4. http://dx.doi.org/10.1002/mcda.476.

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16

Gottschalk, Petter. "System dynamics and multiple-criteria decision making." System Dynamics Review 2, no. 1 (1986): 67. http://dx.doi.org/10.1002/sdr.4260020106.

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17

Peng, Yi, and Lean Yu. "Multiple criteria decision making in emergency management." Computers & Operations Research 42 (February 2014): 1–2. http://dx.doi.org/10.1016/j.cor.2013.08.024.

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18

Siekelova, Anna, Ivana Podhorska, and Jorma J. Imppola. "Analytic Hierarchy Process in Multiple–Criteria Decision–Making: A Model Example." SHS Web of Conferences 90 (2021): 01019. http://dx.doi.org/10.1051/shsconf/20219001019.

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Managers have to make decisions several times a day. The decision-making process can be defined as an essential activity realized by managers every day. Decisions can be implemented intuitively, or by using relevant decision-making methods. This depends on the nature of the decision, as well as the intensity of its possible future effects. The theory of decision-making can be defined as a relatively young discipline. It can be stated that decision-making is no longer an intuitive process. Most decision-making situations are of a multiple criteria character. In this contribution, the authors focus on multiple-criteria decision-making, to which several methods can be applied. In the practical part, the authors use Saaty's method, also known as the Analytic Hierarchy Process. Saaty is considered to be the most important researcher dealing with the issue of multiple-criteria decision-making. The set multiple-criteria decision-making problem was to choose one business partner out of eight under consideration. The decision-making criteria included selected financial indicators and non-financial criteria. The aim of the contribution is to use the Analytic Hierarchy Process to assess potential business partners and to select an optimal candidate.

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19

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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20

Jiang, Yanping, Xia Liang, Manning Li, and Haiming Liang. "Stochastic multiple criteria decision making with criteria 2-tuple aspirations." Soft Computing 23, no. 21 (November 28, 2018): 11167–80. http://dx.doi.org/10.1007/s00500-018-3667-y.

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21

Edwards, Thomas G., and Kenneth R. Chelst. "Purchasing a Used Car Using Multiple Criteria Decision Making." Mathematics Teacher 101, no. 2 (September 2007): 126–35. http://dx.doi.org/10.5951/mt.101.2.0126.

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A Multiple Criteria Decision Making process (MCDM) in which students assign a numerical value to each alternative in a situation, and compute the highest value in order to quantify the optimum choice. MCDM can be used in making decisions such as choosing the best car or right college. This lesson can be used across the mathematics curriculum.

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22

Brožová, H. "The analytic hierarchy process for the decision tree with multiple criteria." Agricultural Economics (Zemědělská ekonomika) 50, No. 2 (February 24, 2012): 77–82. http://dx.doi.org/10.17221/5170-agricecon.

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For choosing the best decision in daily agricultural practice, it is very important to formalize the decision process using systems analysis and mathematical methods. Theory of the decision-making under uncertainty or under risk supposes one criterion. In practice, the best solution is chosen under more decision criteria. Decision problem with <i>m</i> alternatives, <i>n</i> states of nature and k criteria has to be solved in this case. Application of the Analytic Hierarchy Process (AHP) for solution of this problem is described in this paper.

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23

Pearman, Alan, Gerard Colson, and Christian de Bruyn. "Models and Methods in Multiple Criteria Decision Making." Journal of the Operational Research Society 42, no. 3 (March 1991): 262. http://dx.doi.org/10.2307/2583325.

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24

Angehrn, Albert A. "Designing Humanized Systems for Multiple Criteria Decision Making." Human Systems Management 10, no. 3 (1991): 221–31. http://dx.doi.org/10.3233/hsm-1991-10307.

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25

Zeleny, Milan. "Multiple criteria decision making: eight concepts of optimality1." Human Systems Management 17, no. 2 (April 17, 1998): 97–107. http://dx.doi.org/10.3233/hsm-1998-17203.

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Multiple Criteria Decision Making (MCDM) is firmly rooted in an alternative concept of optimality where multiple (rather than single) criteria characterize the notion of “the best” (or optimal), as is prevalent in the areas of economics, engineering, management and business. These are often constrained problems where search for an optimal solution requires some form of evaluating criteria performance tradeoffs. Because there are no tradeoffs along a single criterion, optimality is an essentially multi-criteria concept. In this paper we extend and develop the notion of optimum as a balance among multiple criteria. We introduce eight different, separate and mutually irreducible optimality concepts in a classification scheme where the traditional single-objective optimality is only a special case. These eight optimality concepts provide a useful initiatory framework for the future MCDM research and applications.

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26

Alvarez, Pavel Anselmo, Alessio Ishizaka, and Luis Martínez. "Multiple-criteria decision-making sorting methods: A survey." Expert Systems with Applications 183 (November 2021): 115368. http://dx.doi.org/10.1016/j.eswa.2021.115368.

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27

La Torre, Davide. "Multiple criteria decision making in health and medicine." Journal of Multi-Criteria Decision Analysis 29, no. 1-2 (January 2022): 3–4. http://dx.doi.org/10.1002/mcda.1783.

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28

Green, Rodney H., and John R. Doyle. "On Maximizing Discrimination in Multiple Criteria Decision Making." Journal of the Operational Research Society 46, no. 2 (February 1995): 192. http://dx.doi.org/10.2307/2583988.

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29

Alvisi, F., C. Malagoli, and D. Regazzi. "MULTIFRU: MULTIPLE-CRITERIA DECISION MAKING IN ORCHARD MANAGEMENT." Acta Horticulturae, no. 313 (October 1992): 233–40. http://dx.doi.org/10.17660/actahortic.1992.313.29.

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30

KOU, Gang, Daji ERGU, Yang CHEN, and Changsheng LIN. "PAIRWISE COMPARISON MATRIX IN MULTIPLE CRITERIA DECISION MAKING." Technological and Economic Development of Economy 22, no. 5 (September 2, 2016): 738–65. http://dx.doi.org/10.3846/20294913.2016.1210694.

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The measurement scales, consistency index, inconsistency issues, missing judgment estimation and priority derivation methods have been extensively studied in the pairwise comparison matrix (PCM). Various approaches have been proposed to handle these problems, and made great contributions to the decision making. This paper reviews the literature of the main developments of the PCM. There are plenty of literature related to these issues, thus we mainly focus on the literature published in 37 peer reviewed international journals from 2010 to 2015 (searched via ISI Web of science). We attempt to analyze and classify these literatures so as to find the current hot research topics and research techniques in the PCM, and point out the future directions on the PCM. It is hoped that this paper will provide a comprehensive literature review on PCM, and act as informative summary of the main developments of the PCM for the researchers for their future research.

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31

Holz, Linda, George Kuczera, and Jetse Kalma. "Multiple criteria decision making: Facilitating a learning environment." Journal of Environmental Planning and Management 49, no. 3 (May 2006): 455–70. http://dx.doi.org/10.1080/09640560600601744.

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32

Windle, David. "Multiple Criteria Decision Making Applied To Horse Racing." Teaching Statistics 15, no. 2 (June 1993): 34–37. http://dx.doi.org/10.1111/j.1467-9639.1993.tb00262.x.

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33

BORGULYA†, ISTVAN. "A ranking method for multiple-criteria decision-making." International Journal of Systems Science 28, no. 9 (July 1997): 905–12. http://dx.doi.org/10.1080/00207729708929453.

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34

Munisankaraiah, Dr S., Mr A. Arun Kumar, Mr G. Ravi kumar, and Dr D. K. Pandey. "Multiple Criteria Decision Making Methodology for Network security." International Journal of Computer Trends and Technology 8, no. 1 (February 25, 2014): 17–24. http://dx.doi.org/10.14445/22312803/ijctt-v8p104.

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35

Pearman, Alan. "Models and Methods in Multiple Criteria Decision Making." Journal of the Operational Research Society 42, no. 3 (March 1991): 262. http://dx.doi.org/10.1057/jors.1991.58.

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36

Green, Rodney H., and John R. Doyle. "On Maximizing Discrimination in Multiple Criteria Decision Making." Journal of the Operational Research Society 46, no. 2 (February 1995): 192–204. http://dx.doi.org/10.1057/jors.1995.24.

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37

Rajabi, Siamak, D. Marc Kilgour, and Keith W. Hipel. "Modeling action-interdependence in multiple criteria decision making." European Journal of Operational Research 110, no. 3 (November 1998): 490–508. http://dx.doi.org/10.1016/s0377-2217(97)00318-4.

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38

Campanella, Gianluca, and Rita A. Ribeiro. "A framework for dynamic multiple-criteria decision making." Decision Support Systems 52, no. 1 (December 2011): 52–60. http://dx.doi.org/10.1016/j.dss.2011.05.003.

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39

Lertprapai, S. "Review: multiple criteria decision making method with applications." International Mathematical Forum 8 (2013): 347–55. http://dx.doi.org/10.12988/imf.2013.13033.

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40

Boufateh, Ines, Anne Perwuelz, Besoa Rabenasolo, and Anne Marie Jolly Desodt. "Multiple criteria decision-making for environmental impacts optimisation." International Journal of Business Performance and Supply Chain Modelling 3, no. 1 (2011): 28. http://dx.doi.org/10.1504/ijbpscm.2011.039972.

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41

Ho, William, Prasanta K. Dey, and Helen E. Higson. "Multiple criteria decision‐making techniques in higher education." International Journal of Educational Management 20, no. 5 (August 2006): 319–37. http://dx.doi.org/10.1108/09513540610676403.

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42

Houy, Nicolas, and Koichi Tadenuma. "Lexicographic compositions of multiple criteria for decision making." Journal of Economic Theory 144, no. 4 (July 2009): 1770–82. http://dx.doi.org/10.1016/j.jet.2009.01.009.

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43

Korhonen, Pekka, Herbert Moskowitz, and Jyrki Wallenius. "Choice behavior in interactive multiple-criteria decision making." Annals of Operations Research 23, no. 1 (December 1990): 161–79. http://dx.doi.org/10.1007/bf02204844.

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44

Brauers, W. K. "Multiple criteria decision making in industrial project management." Engineering Costs and Production Economics 20, no. 2 (October 1990): 231–40. http://dx.doi.org/10.1016/0167-188x(90)90106-r.

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45

Doyle, J., and R. Green. "Data envelopment analysis and multiple criteria decision making." Omega 21, no. 6 (November 1993): 713–15. http://dx.doi.org/10.1016/0305-0483(93)90013-b.

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46

Rosinger, Elemér E. "Beyond preference information based multiple criteria decision making." European Journal of Operational Research 53, no. 2 (July 1991): 217–27. http://dx.doi.org/10.1016/0377-2217(91)90136-j.

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47

Köksalan, Murat, Jyrki Wallenius, and Stanley Zionts. "An Early History of Multiple Criteria Decision Making." Journal of Multi-Criteria Decision Analysis 20, no. 1-2 (January 2013): 87–94. http://dx.doi.org/10.1002/mcda.1481.

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48

Zionts, Stanley, and Mark H. Karwan. "A special issue on multiple criteria decision making." Naval Research Logistics 35, no. 6 (December 1988): 539–42. http://dx.doi.org/10.1002/1520-6750(198812)35:6<539::aid-nav3220350603>3.0.co;2-q.

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49

Carlsson, Christer, and Robert Fullér. "Multiple criteria decision making: The case for interdependence." Computers & Operations Research 22, no. 3 (March 1995): 251–60. http://dx.doi.org/10.1016/0305-0548(94)e0023-z.

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50

Peng, Yi, and Yong Shi. "Editorial: Multiple criteria decision making and operations research." Annals of Operations Research 197, no. 1 (February 23, 2012): 1–4. http://dx.doi.org/10.1007/s10479-012-1104-7.

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