Zeitschriftenartikel: „Fuzzy multicriteria decision-making“

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Yager, Ronald R. „Multicriteria Decision-Making Using Fuzzy Measures“. Cybernetics and Systems 46, Nr. 3-4 (03.04.2015): 150–71. http://dx.doi.org/10.1080/01969722.2015.1012884.

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2

Grabisch, Michel. „Fuzzy integral in multicriteria decision making“. Fuzzy Sets and Systems 69, Nr. 3 (Februar 1995): 279–98. http://dx.doi.org/10.1016/0165-0114(94)00174-6.

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3

Zaychenko, Olena Yu, und Yuriy P. Zaychenko. „Multicriteria decision-making problems under fuzzy conditions“. System research and information technologies, Nr. 4 (15.11.2016): 79–87. http://dx.doi.org/10.20535/srit.2308-8893.2016.4.08.

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4

Kahraman, Cengiz, Sezi Cevik Onar und Basar Oztaysi. „Fuzzy Multicriteria Decision-Making: A Literature Review“. International Journal of Computational Intelligence Systems 8, Nr. 4 (Mai 2015): 637–66. http://dx.doi.org/10.1080/18756891.2015.1046325.

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5

Satyadas, Antony, und H. C. Chen. „Multicriteria multigoal decision making - the fuzzy paradigm“. Computers & Industrial Engineering 23, Nr. 1-4 (November 1992): 393–96. http://dx.doi.org/10.1016/0360-8352(92)90144-9.

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6

Rolka, Leszek, Alicja Mieszkowicz-Rolka und Grzegorz Drupka. „Multicriteria decision-making in flight route selection“. Aircraft Engineering and Aerospace Technology 92, Nr. 9 (03.06.2020): 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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Carnero, María Carmen. „Fuzzy Multicriteria Models for Decision Making in Gamification“. Mathematics 8, Nr. 5 (01.05.2020): 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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Ye, Jufeng. „Aggregation Operators of Trapezoidal Intuitionistic Fuzzy Sets to Multicriteria Decision Making“. International Journal of Intelligent Information Technologies 13, Nr. 4 (Oktober 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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Ceballos, Blanca, María Teresa Lamata und David A. Pelta. „Fuzzy Multicriteria Decision-Making Methods: A Comparative Analysis“. International Journal of Intelligent Systems 32, Nr. 7 (20.12.2016): 722–38. http://dx.doi.org/10.1002/int.21873.

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Ponsard, Claude. „Spatial fuzzy consumer's decision making: A multicriteria analysis“. European Journal of Operational Research 25, Nr. 2 (Mai 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 und Jean Couillard. „A fuzzy outranking relation in multicriteria decision making“. European Journal of Operational Research 25, Nr. 2 (Mai 1986): 258–71. http://dx.doi.org/10.1016/0377-2217(86)90090-1.

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Tseng, T. Y., und Cerry M. Klein. „A new algorithm for fuzzy multicriteria decision making“. International Journal of Approximate Reasoning 6, Nr. 1 (Januar 1992): 45–66. http://dx.doi.org/10.1016/0888-613x(92)90039-3.

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Lin, Lin, Xue-Hai Yuan und Zun-Quan Xia. „Multicriteria fuzzy decision-making methods based on intuitionistic fuzzy sets“. Journal of Computer and System Sciences 73, Nr. 1 (Februar 2007): 84–88. http://dx.doi.org/10.1016/j.jcss.2006.03.004.

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Wibowo, Santoso, und Srimannarayana Grandhi. „Benchmarking knowledge management practices in small and medium enterprises“. Benchmarking: An International Journal 24, Nr. 5 (03.07.2017): 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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Tan, Chunqiao, und 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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Goala, Soumendra, und Palash Dutta. „A Fuzzy Multicriteria Decision-Making Approach to Crime Linkage“. International Journal of Information Technologies and Systems Approach 11, Nr. 2 (Juli 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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Wang, Bowen, Haitao Xiong und 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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Chen, Shyi-Ming, Ming-Wey Yang, Szu-Wei Yang, Tian-Wei Sheu und Churn-Jung Liau. „Multicriteria fuzzy decision making based on interval-valued intuitionistic fuzzy sets“. Expert Systems with Applications 39, Nr. 15 (November 2012): 12085–91. http://dx.doi.org/10.1016/j.eswa.2012.04.021.

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Deng, Zhan, und Jianyu Wang. „Evidential Fermatean fuzzy multicriteria decision‐making based on Fermatean fuzzy entropy“. International Journal of Intelligent Systems 36, Nr. 10 (20.06.2021): 5866–86. http://dx.doi.org/10.1002/int.22534.

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Wibowo, Santoso, und Srimannarayana Grandhi. „Fuzzy Multicriteria Analysis for Performance Evaluation of Internet-of-Things-Based Supply Chains“. Symmetry 10, Nr. 11 (07.11.2018): 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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Wang, Xiao-yi, Yi Yang, Yu-ting Bai, Jia-bin Yu, Zhi-yao Zhao und Xue-bo Jin. „Fuzzy Boost Classifier of Decision Experts for Multicriteria Group Decision-Making“. Complexity 2020 (17.08.2020): 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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Cebi, S., und 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, Nr. 4 (28.04.2010): 457–70. http://dx.doi.org/10.1243/09596518jsce874.

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Boucher, T. O., und O. Gogus. „Reliability, validity, and imprecision in fuzzy multicriteria decision-making“. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews) 32, Nr. 3 (August 2002): 190–202. http://dx.doi.org/10.1109/tsmcc.2002.804447.

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Fenton, Norman, und Wei Wang. „Risk and confidence analysis for fuzzy multicriteria decision making“. Knowledge-Based Systems 19, Nr. 6 (Oktober 2006): 430–37. http://dx.doi.org/10.1016/j.knosys.2006.03.002.

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Arslan, Güvenç, und Özlem Aydın. „A NEW SOFTWARE DEVELOPMENT FOR FUZZY MULTICRITERIA DECISION‐MAKING“. Technological and Economic Development of Economy 15, Nr. 2 (30.06.2009): 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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Peneva, Vania, und Ivan Popchev. „Aggregation of fuzzy preference relations to multicriteria decision making“. Fuzzy Optimization and Decision Making 6, Nr. 4 (24.10.2007): 351–65. http://dx.doi.org/10.1007/s10700-007-9018-6.

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Bit, A. K., M. P. Biswal und S. S. Alam. „Fuzzy programming approach to multicriteria decision making transportation problem“. Fuzzy Sets and Systems 50, Nr. 2 (September 1992): 135–41. http://dx.doi.org/10.1016/0165-0114(92)90212-m.

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Yeh, Chung-Hsing, und Yu-Hern Chang. „Modeling subjective evaluation for fuzzy group multicriteria decision making“. European Journal of Operational Research 194, Nr. 2 (April 2009): 464–73. http://dx.doi.org/10.1016/j.ejor.2007.12.029.

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

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Liao, T. Warren. „A fuzzy multicriteria decision-making method for material selection“. Journal of Manufacturing Systems 15, Nr. 1 (Januar 1996): 1–12. http://dx.doi.org/10.1016/0278-6125(96)84211-7.

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Grabisch, Michel. „The application of fuzzy integrals in multicriteria decision making“. European Journal of Operational Research 89, Nr. 3 (März 1996): 445–56. http://dx.doi.org/10.1016/0377-2217(95)00176-x.

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OPRICOVIC, SERAFIM, und GWO-HSHIUNG TZENG. „DEFUZZIFICATION WITHIN A MULTICRITERIA DECISION MODEL“. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 11, Nr. 05 (Oktober 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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Grabisch, Michel. „Alternative Representations of Discrete Fuzzy Measures for Decision Making“. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 05, Nr. 05 (Oktober 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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Wang, Fuqiang, Xihua Li und 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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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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Rashid, Tabasam, Shahzad Faizi und Sohail Zafar. „Distance Based Entropy Measure of Interval-Valued Intuitionistic Fuzzy Sets and Its Application in Multicriteria Decision Making“. Advances in Fuzzy Systems 2018 (17.07.2018): 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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Rashid, Tabasam, und 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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Peng, Juan-juan, Jian-qiang Wang, Jing Wang und 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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Ren, Shapu. „Multicriteria Decision-Making Method Under a Single Valued Neutrosophic Environment“. International Journal of Intelligent Information Technologies 13, Nr. 4 (Oktober 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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Radeva, Irina. „Multicriteria Fuzzy Sets Application in Economic Clustering Problems“. Cybernetics and Information Technologies 17, Nr. 3 (01.09.2017): 29–46. http://dx.doi.org/10.1515/cait-2017-0028.

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Abstract This paper presents an approach for small and medium-sized enterprises selection in economic clusters, where the problem of integration is defined as “ill structured under condition of uncertainty”. The proposed solution demonstrates applying several fuzzy multi-criteria decision making algorithms along with discussion over specific input data requirements. The results are compared with classical multi-criteria decision-making algorithm PROMETHEE II.

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Liu, Shihu, und 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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Wang, Jian-qiang, Xin-E. Li und 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, und 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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Hong, Dug Hun, und Chang-Hwan Choi. „Multicriteria fuzzy decision-making problems based on vague set theory“. Fuzzy Sets and Systems 114, Nr. 1 (August 2000): 103–13. http://dx.doi.org/10.1016/s0165-0114(98)00271-1.

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Wibowo, Santoso. „Evaluating and selecting hospital locations using fuzzy multicriteria decision making“. Asian J. of Management Science and Applications 1, Nr. 3 (2014): 278. http://dx.doi.org/10.1504/ajmsa.2014.064320.

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Zheng, Hanbo, Yiyi Zhang, Junhui Zhao, Jiefeng Liu und Qi Zeng. „Applications of Fuzzy Multicriteria Decision Making to Complex Engineering Problems“. Advances in Fuzzy Systems 2018 (26.12.2018): 1–3. http://dx.doi.org/10.1155/2018/4536234.

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47

Kakati, Pankaj, Surajit Borkotokey, Radko Mesiar und Saifur Rahman. „Interval neutrosophic hesitant fuzzy choquet integral in multicriteria decision making“. Journal of Intelligent & Fuzzy Systems 35, Nr. 3 (01.10.2018): 3213–31. http://dx.doi.org/10.3233/jifs-17166.

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Tan, Chunqiao, und Xiaohong Chen. „Induced intuitionistic fuzzy Choquet integral operator for multicriteria decision making“. International Journal of Intelligent Systems 26, Nr. 7 (19.05.2011): 659–86. http://dx.doi.org/10.1002/int.20489.

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Wang, Weize, und Jerry M. Mendel. „Multicriteria decision making based on intuitionistic fuzzy prioritized arithmetic mean“. International Journal of Intelligent Systems 33, Nr. 7 (23.04.2018): 1412–25. http://dx.doi.org/10.1002/int.21976.

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Chen, Shyi-Ming. „A NEW METHOD FOR HANDLING MULTICRITERIA FUZZY DECISION-MAKING PROBLEMS“. Cybernetics and Systems 25, Nr. 3 (Mai 1994): 409–20. http://dx.doi.org/10.1080/01969729408902336.

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