Journal articles: 'Fuzzy multicriteria decision-making'

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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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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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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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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 linguistic criteria are integrated into a crisp decision matrix for determining the final ranking using the technique for order preferences by similarity to an ideal solution (TOPSIS) method. Findings The considered decision-making problem involves different kinds of criteria. Numerical (objective) criteria are given as real numbers. Linguistic (subjective) criteria are expressed with the help of fuzzy linguistic values. In consequence, a (logical) reasoning process prior to performing an (arithmetic) optimization procedure is necessary. Furthermore, a uniform optimization procedure requires a way of combining numerical and linguistic attributes. Practical implications The proposed approach can be applied to solving various multicriteria decision-making problems, where both objective and subjective criteria are taken into account. Originality/value First, a fuzzy information system that includes linguistic condition attributes is constructed. Second, a fuzzy inference system that is necessary for determining the resulting fuzzy criterion “turbulence conditions” for all flight routes is introduced. Finally, a way of combining numerical and linguistic criteria is proposed. This is done by converting values of fuzzy attributes into crisp ones, basing on the preferences of a decision-maker.

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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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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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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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Ye, Jufeng. "Aggregation Operators of Trapezoidal Intuitionistic Fuzzy Sets to Multicriteria Decision Making." International Journal of Intelligent Information Technologies 13, no. 4 (2017): 1–22. http://dx.doi.org/10.4018/ijiit.2017100101.

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This paper presents the trapezoidal intuitionistic fuzzy weighted averaging (TIFWA) operator, trapezoidal intuitionistic fuzzy ordered weighted averaging (TIFOWA) operator, trapezoidal intuitionistic fuzzy weighted geometric (TIFWG) operator, and trapezoidal intuitionistic fuzzy ordered weighted geometric (TIFOWG) operator to aggregate the trapezoidal intuitionistic fuzzy information and investigates their properties. Furthermore, a multicriteria decision making method based on the TIFOWA and TIFOWG operators and the score function and accuracy function of a trapezoidal intuitionistic fuzzy number is established to deal with the multicriteria decision making problem with trapezoidal intuitionistic fuzzy information. Finally, an illustrative example demonstrates the application of the proposed method.

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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 for representing the subjective assessments of decision makers in evaluating the relative importance of the evaluation criteria and the performance of individual KM practices with respect to specific evaluation criteria. A fuzzy multicriteria group decision-making algorithm is developed for measuring and benchmarking the performance of alternative KM practices. Findings The proposed multicriteria group decision-making approach is capable of effectively evaluating the performance of KM practices through adequately considering the presence of multiple decision makers, the multi-dimensional nature of the evaluation problem, and appropriately modeling the subjectiveness and imprecision of the evaluation process. The presentation of an example shows that the proposed fuzzy multicriteria group decision-making algorithm is simple to use and efficient in computation. Research limitations/implications The outcome of the multicriteria group decision-making approach is highly dependent on the inputs provided by the decision maker. Practical implications The novelty from this research lies in the utilization of a multicriteria group decision-making approach for evaluating the performance of KM practices in an organization. The outcome from the performance evaluation process allows the enterprise to adopt appropriate KM practices for achieving competitive advantages. Social implications The proposed multicriteria group decision-making approach has a significant social implication as it can be used as a decision-making tool for providing various decision makers in SMEs with useful and strategic information concerning the performance of KM practices in a given situation. Originality/value The originality of this paper lies in the development of the multicriteria group decision-making approach for effectively measuring and benchmarking the performance of KM practices of individual SMEs.

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Carnero, María Carmen. "Fuzzy Multicriteria Models for Decision Making in Gamification." Mathematics 8, no. 5 (2020): 682. http://dx.doi.org/10.3390/math8050682.

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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.

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Tan, Chunqiao, and Xiaohong Chen. "Interval-Valued Intuitionistic Fuzzy Multicriteria Group Decision Making Based on VIKOR and Choquet Integral." Journal of Applied Mathematics 2013 (2013): 1–16. http://dx.doi.org/10.1155/2013/656879.

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An effective decision making approach based on VIKOR and Choquet integral is developed to solve multicriteria group decision making problem with conflicting criteria and interdependent subjective preference of decision makers in a fuzzy environment where preferences of decision makers with respect to criteria are represented by interval-valued intuitionistic fuzzy sets. First, an interval-valued intuitionistic fuzzy Choquet integral operator is given. Some of its properties are investigated in detail. The extended VIKOR decision procedure based on the proposed operator is developed for solving the multicriteria group decision making problem where the interactive criteria weight is measured by Shapley value. An illustrative example is given for demonstrating the applicability of the proposed decision procedure for solving the multi-criteria group decision making problem in interval-valued intuitionistic fuzzy environment.

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Remad, Fedia Daami, and Hela Moalla Frikha. "The multicriteria group decision making FlowSort method under uncertainty." Multiple Criteria Decision Making 16 (2021): 122–39. http://dx.doi.org/10.22367/mcdm.2021.16.07.

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Crisp values are insufficient to model real-life situations and imprecise ideas are frequently represented in multicriteria decision aid analysis. In fact, it is difficult to treat the evaluation criteria precisely and to fix exact preferences rating. The triangular intuitionistic fuzzy numbers succeeded to treat this kind of ambiguity in a great deal of research than other forms of fuzzy representation functions. The field of sorting issues is an active research topic in the multiple criteria decision aid (MCDA). This study extended one of the sorting methods, FLOWSORT, for solving multiple criteria group decision-making problems. This extension described the preferences rating of alternatives as linguistic terms which can be easily expressed in triangular intuitionistic fuzzy numbers. To validate our extension, an illustrative example as well as an empirical comparison with other multi-criteria decision making methods is presented. Keywords: multicriteria group decision making, sorting problematic, intuitionistic fuzzy set, FlowSort method

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Wibowo, Santoso, and Srimannarayana Grandhi. "Fuzzy Multicriteria Analysis for Performance Evaluation of Internet-of-Things-Based Supply Chains." Symmetry 10, no. 11 (2018): 603. http://dx.doi.org/10.3390/sym10110603.

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This paper presents a fuzzy multicriteria analysis model for evaluating the performance of Internet of Things (IoT)-based supply chains. The inherent uncertainty and imprecision of the performance evaluation process was handled by using intuitionistic fuzzy numbers. A new fuzzy multicriteria group decision making algorithm based on the technique ordered preference by similarity to the ideal solution (TOPSIS) approach, and the concept of similarity measures was developed for determining the overall performance of each alternative. The advantage of the proposed fuzzy multicriteria analysis model is that it can overcome the limitations of the existing approaches in an intuitionistic fuzzy environment. The fuzzy multicriteria group decision-making model provides organizations with the ability to evaluate the performance of their IoT-based supply chains for improving their competitiveness. An example is presented to highlight the usefulness of the proposed model for tackling a real world IoT performance evaluation problem.

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Lin, Lin, Xue-Hai Yuan, and Zun-Quan Xia. "Multicriteria fuzzy decision-making methods based on intuitionistic fuzzy sets." Journal of Computer and System Sciences 73, no. 1 (2007): 84–88. http://dx.doi.org/10.1016/j.jcss.2006.03.004.

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Tseng, T. Y., and Cerry M. Klein. "A new algorithm for fuzzy multicriteria decision making." International Journal of Approximate Reasoning 6, no. 1 (1992): 45–66. http://dx.doi.org/10.1016/0888-613x(92)90039-3.

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Ponsard, Claude. "Spatial fuzzy consumer's decision making: A multicriteria analysis." European Journal of Operational Research 25, no. 2 (1986): 235–46. http://dx.doi.org/10.1016/0377-2217(86)90088-3.

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Martel, Jean-Marc, Gilles R. D'Avignon, and Jean Couillard. "A fuzzy outranking relation in multicriteria decision making." European Journal of Operational Research 25, no. 2 (1986): 258–71. http://dx.doi.org/10.1016/0377-2217(86)90090-1.

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Ceballos, Blanca, María Teresa Lamata, and David A. Pelta. "Fuzzy Multicriteria Decision-Making Methods: A Comparative Analysis." International Journal of Intelligent Systems 32, no. 7 (2016): 722–38. http://dx.doi.org/10.1002/int.21873.

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Wang, Bowen, Haitao Xiong, and Chengrui Jiang. "A Multicriteria Decision Making Approach Based on Fuzzy Theory and Credibility Mechanism for Logistics Center Location Selection." Scientific World Journal 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/347619.

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As a hot topic in supply chain management, fuzzy method has been widely used in logistics center location selection to improve the reliability and suitability of the logistics center location selection with respect to the impacts of both qualitative and quantitative factors. However, it does not consider the consistency and the historical assessments accuracy of experts in predecisions. So this paper proposes a multicriteria decision making model based on credibility of decision makers by introducing priority of consistency and historical assessments accuracy mechanism into fuzzy multicriteria decision making approach. In this way, only decision makers who pass the credibility check are qualified to perform the further assessment. Finally, a practical example is analyzed to illustrate how to use the model. The result shows that the fuzzy multicriteria decision making model based on credibility mechanism can improve the reliability and suitability of site selection for the logistics center.

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Rashid, Tabasam, Shahzad Faizi, and Sohail Zafar. "Distance Based Entropy Measure of Interval-Valued Intuitionistic Fuzzy Sets and Its Application in Multicriteria Decision Making." Advances in Fuzzy Systems 2018 (July 17, 2018): 1–10. http://dx.doi.org/10.1155/2018/3637897.

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Fuzzy entropy means the measurement of fuzziness in a fuzzy set and therefore plays a vital role in solving the fuzzy multicriteria decision making (MCDM) and multicriteria group decision making (MCGDM) problems. In this study, the notion of the measure of distance based entropy for uncertain information in the context of interval-valued intuitionistic fuzzy set (IVIFS) is introduced. The arithmetic and geometric average operators are firstly used to aggregate the interval-valued intuitionistic fuzzy information provided by the decision makers (DMs) or experts corresponding to each alternative, and then the fuzzy entropy of each alternative is calculated based on proposed distance measure. Several numerical examples are solved to demonstrate the application to MCDM and MCGDM problems to show the effectiveness of the proposed approach.

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Bai, Zhi-yong. "An Interval-Valued Intuitionistic Fuzzy TOPSIS Method Based on an Improved Score Function." Scientific World Journal 2013 (2013): 1–6. http://dx.doi.org/10.1155/2013/879089.

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This paper proposes an improved score function for the effective ranking order of interval-valued intuitionistic fuzzy sets (IVIFSs) and an interval-valued intuitionistic fuzzy TOPSIS method based on the score function to solve multicriteria decision-making problems in which all the preference information provided by decision-makers is expressed as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by IVIFS value and the information about criterion weights is known. We apply the proposed score function to calculate the separation measures of each alternative from the positive and negative ideal solutions to determine the relative closeness coefficients. According to the values of the closeness coefficients, the alternatives can be ranked and the most desirable one(s) can be selected in the decision-making process. Finally, two illustrative examples for multicriteria fuzzy decision-making problems of alternatives are used as a demonstration of the applications and the effectiveness of the proposed decision-making method.

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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 is classified into some criteria. Patients’ states and weights for the existing symptoms are assumed as vague point entries. As a mathematical tool, the present model used vague relations for illustrating different associations like symptom criteria and diseases and the state of the patients. The present model also discusses confidence interval-based statistical analysis for the construction of TVNs, which are the prominent component of the study. Findings: A numerical computation is illustrated with the whole procedure of the decision-making. To show the capability and distinctness of the proposed methodology, a comparative discussion for outcomes is given. The present method coincides with the existing fuzzy-based method for the initial diagnosis, while possibility degrees of diagnoses differences for patient P1 and patient P2 differ. It ranges from 1% to 16.3% in the method based on the existing traditionally fuzzy approach, and in the present approach, these differences range from 2.15% to 7.46%. Novelty: This research contributes to presenting a novel decision expert system that is more capable of making diagnosis efficient. This study provides a practical and visual tool to assess potential outcomes of the proposed technique through a numerical example. Keywords: Vague set, Lower and upper membership function, Vague point, Trapezoidal vague number, Medical diagnosis

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Goala, Soumendra, and Palash Dutta. "A Fuzzy Multicriteria Decision-Making Approach to Crime Linkage." International Journal of Information Technologies and Systems Approach 11, no. 2 (2018): 31–50. http://dx.doi.org/10.4018/ijitsa.2018070103.

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This article describes how serial crimes are very interesting for study in the absence of proper and solid evidence. From a high volume of criminal cases of similar types, it is difficult to detect the crimes that were committed by the same offender or not. The process of linking of crimes which were committed by the same offender or offenders is called Crime Linkage Analysis. In this article, a new hesitant fuzzy distance measure has been introduced and a fuzzy multicriteria decision-making approach has been proposed to help Crime Linkage Analysis, which enables us to find to what extent a pair of crime shares a common offender or offenders.

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Ibrahim, Hariwan Z., Tareq M. Al-Shami, and Abdelwaheb Mhemdi. "Applications of nth Power Root Fuzzy Sets in Multicriteria Decision Making." Journal of Mathematics 2023 (March 29, 2023): 1–14. http://dx.doi.org/10.1155/2023/1487724.

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An nth power root fuzzy set is a useful extension of a fuzzy set for expressing uncertain data. Because of their wider range of showing membership grades, nth power root fuzzy sets can cover more ambiguous situations than intuitionistic fuzzy sets. In this article, we present several novel operations on nth power root fuzzy sets, as well as their various features. Besides, we develop a new weighted aggregated operator, namely, nth power root fuzzy weighted power average (nPR-FWPA) over nth power root fuzzy sets to deal with choice information and show some of their basic properties. In addition, we define a scoring function for nth power root fuzzy sets ranking. Furthermore, we use this operator to determine the optimal location for constructing a home and demonstrate how we may choose the best alternative by comparing aggregate outputs using score values. Finally, we compare the nPR-FWPA operator outcomes to those of other well-known operators.

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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 overcomes the issues that arise while taking decisions. This study involves the development of structural hierarchical models of parameters and the implementation of soft expert sets to make the decision-making problem much more precise by introducing a new algorithm. Thus, this model is helpful for multicriteria decision making and can be used for university selection and thus suitable for education sector as well.

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OPRICOVIC, SERAFIM, and GWO-HSHIUNG TZENG. "DEFUZZIFICATION WITHIN A MULTICRITERIA DECISION MODEL." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 11, no. 05 (2003): 635–52. http://dx.doi.org/10.1142/s0218488503002387.

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In many cases, criterion values are crisp in nature, and their values are determined by economic instruments, mathematical models, and/or by engineering measurement. However, there are situations when the evaluation of alternatives must include the imprecision of established criteria, and the development of a fuzzy multicriteria decision model is necessary to deal with either "qualitative" (unquantifiable or linguistic) or incomplete information. The proposed fuzzy multicriteria decision model (FMCDM) consists of two phases: the CFCS phase - Converting the Fuzzy data into Crisp Scores, and the MCDM phase - MultiCriteria Decision Making. This model is applicable for defuzzification within the MCDM model with a mixed set of crisp and fuzzy criteria. A newly developed CFCS method is based on the procedure of determining the left and right scores by fuzzy min and fuzzy max, respectively, and the total score is determined as a weighted average according to the membership functions. The advantage of this defuzzification method is illustrated by some examples, comparing the results from three considered methods.

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Wang, Fuqiang, Xihua Li, and Xiaohong Chen. "Hesitant Fuzzy Soft Set and Its Applications in Multicriteria Decision Making." Journal of Applied Mathematics 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/643785.

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Molodtsov’s soft set theory is a newly emerging mathematical tool to handle uncertainty. However, the classical soft sets are not appropriate to deal with imprecise and fuzzy parameters. This paper aims to extend the classical soft sets to hesitant fuzzy soft sets which are combined by the soft sets and hesitant fuzzy sets. Then, the complement, “AND”, “OR”, union and intersection operations are defined on hesitant fuzzy soft sets. The basic properties such as DeMorgan’s laws and the relevant laws of hesitant fuzzy soft sets are proved. Finally, with the help of level soft set, the hesitant fuzzy soft sets are applied to a decision making problem and the effectiveness is proved by a numerical example.

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Deng, Zhan, and Jianyu Wang. "Evidential Fermatean fuzzy multicriteria decision‐making based on Fermatean fuzzy entropy." International Journal of Intelligent Systems 36, no. 10 (2021): 5866–86. http://dx.doi.org/10.1002/int.22534.

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Chen, Shyi-Ming, Ming-Wey Yang, Szu-Wei Yang, Tian-Wei Sheu, and Churn-Jung Liau. "Multicriteria fuzzy decision making based on interval-valued intuitionistic fuzzy sets." Expert Systems with Applications 39, no. 15 (2012): 12085–91. http://dx.doi.org/10.1016/j.eswa.2012.04.021.

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Rashid, Tabasam, and Syed Muhammad Husnine. "Multicriteria Group Decision Making by Using Trapezoidal Valued Hesitant Fuzzy Sets." Scientific World Journal 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/304834.

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The concept of trapezoidal valued hesitant fuzzy set is introduced. Notion for distance between any two trapezoidal valued hesitant fuzzy elements is given. Using this proposed distance measure, we extend the technique for order preference by similarity to ideal solution for trapezoidal valued hesitant fuzzy sets. An example is constructed to show usefulness of this extension for multicriteria group decision making, where the opinions about the criteria values are expressed as trapezoidal valued hesitant fuzzy set.

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Wang, Xiao-yi, Yi Yang, Yu-ting Bai, Jia-bin Yu, Zhi-yao Zhao, and Xue-bo Jin. "Fuzzy Boost Classifier of Decision Experts for Multicriteria Group Decision-Making." Complexity 2020 (August 17, 2020): 1–10. http://dx.doi.org/10.1155/2020/8147617.

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The expert is a vital role in multicriteria decision-making, which provides source decision opinions. In the existing group decision-making activities, the selection of experts is usually conducted artificially, which relies on personal subjective experience. It has been the urgent demand for an automatic selection of experts, which can help to determine their weights for the follow-up decision calculation. In this paper, an expert classification method is proposed to solve the problem. First, the CatBoost classification algorithm is improved by integrating the 2-tuple linguistic, which can effectively extract the features of samples. Second, the framework of the expert classification is designed. The flow combines the expert resume collection, expert classification, and database update. Third, a decision-making case is analyzed for the expert selection issue. The experiment and result indicate that the proposed classifier performs better than the classic methods. The proposed classification method of the decision experts can support the automatic and intelligent operation of the decision-making activities.

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Liu, Shihu, and Tauqir Ahmed Moughal. "A Novel Method for Dynamic Multicriteria Decision Making with Hybrid Evaluation Information." Journal of Applied Mathematics 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/864628.

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How to select the most desirable pattern(s) is often a crucial step for decision making problem. By taking uncertainty as well as dynamic of database into consideration, in this paper, we construct a dynamic multicriteria decision making procedure, where the evaluation information of criteria is expressed by real number, intuitionistic fuzzy number, and interval-valued intuitionistic fuzzy number. During the process of algorithm construction, the evaluation information at all time episodes is firstly aggregated into one, and then it is transformed into the unified interval-valued intuitionistic fuzzy number representational form. Similar to most multicriteria decision making approaches, the TOPSIS method is applied in the proposed decision making algorithm. In particular, the distance between possible patterns and the ideal solutions is defined in terms of cosine similarity by considering all aspects of the unified evaluation information. Experimental results show that the proposed decision making approach can effectively select desirable pattern(s).

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Grabisch, Michel. "Alternative Representations of Discrete Fuzzy Measures for Decision Making." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 05, no. 05 (1997): 587–607. http://dx.doi.org/10.1142/s0218488597000440.

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This paper introduces three different representations of fuzzy measures, through the Möbius transformation, and the expression of importance and interaction. This leads naturally to the concept of k-order additive measures. It is shown how these concepts can be used in decision making, especially multicriteria evaluation.

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Peng, Juan-juan, Jian-qiang Wang, Jing Wang, and Xiao-hong Chen. "Multicriteria Decision-Making Approach with Hesitant Interval-Valued Intuitionistic Fuzzy Sets." Scientific World Journal 2014 (2014): 1–22. http://dx.doi.org/10.1155/2014/868515.

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The definition of hesitant interval-valued intuitionistic fuzzy sets (HIVIFSs) is developed based on interval-valued intuitionistic fuzzy sets (IVIFSs) and hesitant fuzzy sets (HFSs). Then, some operations on HIVIFSs are introduced in detail, and their properties are further discussed. In addition, some hesitant interval-valued intuitionistic fuzzy number aggregation operators based ont-conorms andt-norms are proposed, which can be used to aggregate decision-makers' information in multicriteria decision-making (MCDM) problems. Some valuable proposals of these operators are studied. In particular, based on algebraic and Einsteint-conorms andt-norms, some hesitant interval-valued intuitionistic fuzzy algebraic aggregation operators and Einstein aggregation operators can be obtained, respectively. Furthermore, an approach of MCDM problems based on the proposed aggregation operators is given using hesitant interval-valued intuitionistic fuzzy information. Finally, an illustrative example is provided to demonstrate the applicability and effectiveness of the developed approach, and the study is supported by a sensitivity analysis and a comparison analysis.

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Cebi, S., and C. Kahraman. "Fuzzy multicriteria group decision making for real estate investments." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 224, no. 4 (2010): 457–70. http://dx.doi.org/10.1243/09596518jsce874.

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Arslan, Güvenç, and Özlem Aydın. "A NEW SOFTWARE DEVELOPMENT FOR FUZZY MULTICRITERIA DECISION‐MAKING." Technological and Economic Development of Economy 15, no. 2 (2009): 197–212. http://dx.doi.org/10.3846/1392-8619.2009.15.197-212.

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In this paper, software for Fuzzy Multiple Criteria Decision Making (FMCDM) problems has been developed and tested on two real problems. FMCDM methods are widely used when imprecise data or linguistic variables exist in the problem. Using FMCDM methods may help improve decision‐making problems and lead to more accurate models. Although these methods are more involved in terms of computing due to fuzzy calculations in MCDM algorithms, fuzziness offers advantages over classical algorithms. Thus appropriate software is of great importance in applying FMCDM methods. The major aim of this study is to develop software and to test it on two real military problems which are solved by an ideal points algorithm and an outranking method. The results and outputs are discussed with sensitivity analyses. Santrauka Aprašomos programos, skirtos daugiakriteriniam sprendimų priėmimui esant neapibrėžtumams, kūrimas ir jos pritaikymas sprendžiant dvi realias problemas. Neapibrėžtųjų aibių daugiakriteriniai metodai plačiai taikomi, kai esama netikslių duomenų arba lingvistinių kintamųjų. Taikant šiuos metodus galima lengviau išspręsti sprendimo priėmimo problemas, sudaryti tikslesnius modelius. Nors tokiu atveju reikia daugiau skaičiavimų siekiant taikyti neapibrėžtąsias aibes daugiakriteriniuose sprendimų priėmimo algoritmuose, tačiau galimybė įvertinti neapibrėžtumus suteikia pranašumų, palyginti su klasikiniais metodais. Taigi neapibrėžtųjų aibių daugiakriteriniams metodams labai svarbu tinkama programinė įranga. Svarbiausias šio tyrimo tikslas – sukurti programinę įrangą ir testuoti ją sprendžiant dvi tikras karines problemas – idealiųjų taškų agoritmą ir rangavimų metodą. Rezultatai aptarti atlikus jautrumo analizę.

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Boucher, T. O., and O. Gogus. "Reliability, validity, and imprecision in fuzzy multicriteria decision-making." IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews) 32, no. 3 (2002): 190–202. http://dx.doi.org/10.1109/tsmcc.2002.804447.

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Fenton, Norman, and Wei Wang. "Risk and confidence analysis for fuzzy multicriteria decision making." Knowledge-Based Systems 19, no. 6 (2006): 430–37. http://dx.doi.org/10.1016/j.knosys.2006.03.002.

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Yeh, Chung-Hsing, and Yu-Hern Chang. "Modeling subjective evaluation for fuzzy group multicriteria decision making." European Journal of Operational Research 194, no. 2 (2009): 464–73. http://dx.doi.org/10.1016/j.ejor.2007.12.029.

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Bit, A. K., M. P. Biswal, and S. S. Alam. "Fuzzy programming approach to multicriteria decision making transportation problem." Fuzzy Sets and Systems 50, no. 2 (1992): 135–41. http://dx.doi.org/10.1016/0165-0114(92)90212-m.

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Liao, T. Warren. "A fuzzy multicriteria decision-making method for material selection." Journal of Manufacturing Systems 15, no. 1 (1996): 1–12. http://dx.doi.org/10.1016/0278-6125(96)84211-7.

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Tan, Chunqiao, Wentao Yi, and Xiaohong Chen. "Hesitant fuzzy Hamacher aggregation operators for multicriteria decision making." Applied Soft Computing 26 (January 2015): 325–49. http://dx.doi.org/10.1016/j.asoc.2014.10.007.

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Grabisch, Michel. "The application of fuzzy integrals in multicriteria decision making." European Journal of Operational Research 89, no. 3 (1996): 445–56. http://dx.doi.org/10.1016/0377-2217(95)00176-x.

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Salehi, Sara. "A Fuzzy Multicriteria Decision Making Approach in Higher Education." International Journal of Computing and Digital Systems 14, no. 1 (2023): 10159–68. http://dx.doi.org/10.12785/ijcds/140189.

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Peneva, Vania, and Ivan Popchev. "Aggregation of fuzzy preference relations to multicriteria decision making." Fuzzy Optimization and Decision Making 6, no. 4 (2007): 351–65. http://dx.doi.org/10.1007/s10700-007-9018-6.

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Chang, Zaibin, and Lingling Mao. "Some New Covering-Based Multigranulation Fuzzy Rough Sets and Corresponding Application in Multicriteria Decision Making." Journal of Mathematics 2021 (November 19, 2021): 1–25. http://dx.doi.org/10.1155/2021/6937307.

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Multigranulation rough set theory is an important tool to deal with the problem of multicriteria information system. The notion of fuzzy β -neighborhood has been used to construct some covering-based multigranulation fuzzy rough set (CMFRS) models through multigranulation fuzzy measure. But the β -neighborhood has not been used in these models, which can be seen as the bridge of fuzzy covering-based rough sets and covering-based rough sets. In this paper, the new concept of multigranulation fuzzy neighborhood measure and some types of covering-based multigranulation fuzzy rough set (CMFRS) models based on it are proposed. They can be seen as the further combination of fuzzy sets: covering-based rough sets and multigranulation rough sets. Moreover, they are used to solve the problem of multicriteria decision making. Firstly, the definition of multigranulation fuzzy neighborhood measure is given based on the concept of β -neighborhood. Moreover, four types of CMFRS models are constructed, as well as their characteristics and relationships. Then, novel matrix representations of them are investigated, which can satisfy the need of knowledge discovery from large-scale covering information systems. The matrix representations can be more easily implemented than set representations by computers. Finally, we apply them to manage the problem of multicriteria group decision making (MCGDM) and compare them with other methods.

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Fedia, Remadi Daami, and Frikha Moalla Hela. "The Intuitionistic Fuzzy FlowSort Method for Multicriteria Group Decision Making." International Journal of Fuzzy System Applications 11, no. 1 (2022): 1–21. http://dx.doi.org/10.4018/ijfsa.285554.

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The real life problems are multidimensional in nature and may involve some ambiguity when it comes to decision making. It is, therefore, difficult to design the evaluation criteria precisely and determine the exact value of the attributes in the multicriteria analysis. The intuitionistic fuzzy set (IFS) achieved great success in treating this kind of ambiguity in a great deal of research. The study of sorting problems is an active research issue in the multiple criteria decision aid (MCDA) area. This paper investigated one of the sorting methods, FLOWSORT, and extended it to the multicriteria group decision making based on the output aggregation of the individual sorting results. The rating of each alternative was described through linguistic terms that can be expressed in triangular intuitionistic fuzzy numbers. An illustrative example as well as an empirical comparison with other multi-criteria decision making methods were carried out to validate our extension.

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Ren, Shapu. "Multicriteria Decision-Making Method Under a Single Valued Neutrosophic Environment." International Journal of Intelligent Information Technologies 13, no. 4 (2017): 23–37. http://dx.doi.org/10.4018/ijiit.2017100102.

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A single valued neutrosophic set (SVNS) is a subclass of neutrosophic sets, which generalizes fuzzy sets, interval valued fuzzy set, and intuitionistic fuzzy set. It can be used to easily express incomplete, indeterminate and inconsistent information. This paper introduces the Dice similarity measure of single valued neutrosophic numbers (SVNNs) for ranking SVNNs and a single valued neutrosophic prioritized weighted geometric (SVNPWG) operator for aggregating single valued neutrosophic information. Based on the SVNPWG operator and the Dice similarity measure for SVNNs, a multicriteria decision-making method with different priority levels in the criteria is established in which the evaluation values of alternatives with respective to criteria are represented in the form of SVNNs. The ranking order of alternatives is performed through the Dice measure and the best one(s) can be determined as well. Finally, an illustrative example shows the application of the proposed method.

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Wang, Jian-qiang, Xin-E. Li, and Xiao-hong Chen. "Hesitant Fuzzy Soft Sets with Application in Multicriteria Group Decision Making Problems." Scientific World Journal 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/806983.

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Soft sets have been regarded as a useful mathematical tool to deal with uncertainty. In recent years, many scholars have shown an intense interest in soft sets and extended standard soft sets to intuitionistic fuzzy soft sets, interval-valued fuzzy soft sets, and generalized fuzzy soft sets. In this paper, hesitant fuzzy soft sets are defined by combining fuzzy soft sets with hesitant fuzzy sets. And some operations on hesitant fuzzy soft sets based on Archimedean t-norm and Archimedean t-conorm are defined. Besides, four aggregation operations, such as the HFSWA, HFSWG, GHFSWA, and GHFSWG operators, are given. Based on these operators, a multicriteria group decision making approach with hesitant fuzzy soft sets is also proposed. To demonstrate its accuracy and applicability, this approach is finally employed to calculate a numerical example.

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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 is not observed. Rank-reversal is a paradoxical feature in the decision-making methods, which is caused by determining the absolute evaluations of considered alternatives on the basis of the alternatives themselves. In the Analytic Hierarchy Process (AHP) method and similar methods, when a new alternative is added to the original alternative set, the evaluation base and the resulting evaluations of all objects change. A great advantage of the COMET is its ability to identify not only linear but also nonlinear multicriteria models of decision makers. This identification is based not on a ranking of component criteria of the multicriterion but on a ranking of a larger set of characteristic objects (characteristic alternatives) that are independent of the small set of alternatives analyzed in a given problem. As a result, the COMET is free of the faults of other methods.

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Journal articles on the topic 'Fuzzy multicriteria decision-making'

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