Journal articles: 'Fuzzy judgments'

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Saaty, Thomas L., and Liem T. Tran. "Fuzzy Judgments and Fuzzy Sets." International Journal of Strategic Decision Sciences 1, no. 1 (January 2010): 23–40. http://dx.doi.org/10.4018/jsds.2010103002.

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Using fuzzy set theory has become attractive to many people. However, the many references cited here and in other works, little thought is given to why numbers should be made fuzzy before plunging into the necessary simulations to crank out numbers without giving reason or proof that it works to one’s advantage. In fact it does not often do that, certainly not in decision making. Regrettably, many published papers that use fuzzy set theory presumably to get better answers were not judged thoroughly by reviewers knowledgeable in both fuzzy theory and decision making. Buede and Maxwell (1995), who had done experiments on different ways of making decisions, found that fuzzy does the poorest job of obtaining the right decision as compared with other ways. “These experiments demonstrated that the MAVT (Multiattribute Value Theory) and AHP (Analytic Hierarchy Process) techniques, when provided with the same decision outcome data, very often identify the same alternatives as ‘best’. The other techniques are noticeably less consistent with the Fuzzy algorithm being the least consistent.”

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Posadsky, Alexey Igorevich, Tatiana Vladimirovna Sivakova, and Vladimir Anatolievich Sudakov. "Aggregation of Fuzzy Expert Judgments." Keldysh Institute Preprints, no. 101 (2019): 1–12. http://dx.doi.org/10.20948/prepr-2019-101.

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GHAZANFARI, MEHDI, and MAJID NOJAVAN. "EDUCING INCONSISTENCY IN FUZZY AHP BY MATHEMATICAL PROGRAMMING MODELS." Asia-Pacific Journal of Operational Research 21, no. 03 (September 2004): 379–91. http://dx.doi.org/10.1142/s0217595904000291.

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The inconsistency of judgments in the fuzzy Analytic Hierarchy Process (AHP) is a crucial issue. To make the appropriate decision, the inconsistency in decision maker's (DM) judgments needs to be eliminated or reduced. This paper proposes two mathematical models to deal with inconsistency in fuzzy AHP. In the first model, the DM's judgments are modified where the preference order of the DM's judgments remained unchanged. The second model allows reversing the preference orders of judgments. The proposed models aim to eliminate or reduce the inconsistency of fuzzy AHP by changing judgments. The models cause fewer changes for the high certain judgments. Two examples solved by the proposed models are included for purposes of illustration.

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Yang, Jing. "Synthesizing Different Preference Information by Fuzzy Programming Method." Advanced Materials Research 328-330 (September 2011): 2352–57. http://dx.doi.org/10.4028/www.scientific.net/amr.328-330.2352.

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Group decision making problems with different forms of preference information are discussed. Firstly, four forms of preference information ( i.e. preference ordering, utility value, AHP judgment matrix and fuzzy judgment matrix) are introduced and the computing formulas are given to transform different forms of preference information into the form of fuzzy judgment matrix. A new method that involves in different preference strength of experts is studied. Then, the assessment of the group priorities is formulated as a fuzzy linear programming problem, maximizing the group’s overall satisfaction to get the group solution. The method can easily deal with missing judgments and different partiality intensity by decision makers. At the end, the feasibility and effectiveness of method is explained by an example.

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Sudakov, V., and T. Sivakova. "Features of aggregation of fuzzy expert judgments." IOP Conference Series: Materials Science and Engineering 927 (September 26, 2020): 012034. http://dx.doi.org/10.1088/1757-899x/927/1/012034.

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Vicente, E., A. Mateos, and A. Jiménez-Martín. "A Betting- and Lottery-Based Method for Fuzzy Probability Elicitation." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 27, no. 01 (February 2019): 121–44. http://dx.doi.org/10.1142/s0218488519500065.

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It is very common to use linguistic term scales, whose terms are previously associated with different fuzzy numbers to assign probabilities to events in decision-making processes. However, the rigidity of such scales generates bias in the probability elicitation process and does not allow experts to adequately express their probabilistic judgments. We propose a betting and lottery-based method for eliciting a fuzzy number from the expert that represents his/her probabilistic judgments for a given event, along with a quality measure of the probabilistic judgments based on precision and consistency measures. We also enact a simulation process to analyze possible biases in the proposed fuzzy probability elicitation method.

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Simanihuruk, Tiarma, H. Hartono, Dahlan Abdullah, Cut Ita Erliana, Darmawan Napitupulu, Erianto Ongko, Robbi Rahim, Sukiman ., and Ansari Saleh Ahmar. "Hesitant Fuzzy Linguistic Term Sets with Fuzzy Grid Partition in Determining the Best Lecturer." International Journal of Engineering & Technology 7, no. 2.3 (March 8, 2018): 59. http://dx.doi.org/10.14419/ijet.v7i2.3.12322.

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Decision-making on conditions that involve many alternatives, many criteria, and many judgments is a difficult thing to do. The difficulty is coupled with assessors who sometimes make decisions in hesitant, unclear, and inconsistent circumstances and each person can provide different judgments. One of the methods that can be used is Hesitant Fuzzy Linguistic Term Sets which is the development of Fuzzy Sets that can make decisions by using Hesitant Fuzzy Sets. Hesitant linguistic term has been introduced for capturing the human way of reasoning using linguistic expressions involving different levels of precision. The integration of Hesitant Fuzzy Linguistic Term Sets with Fuzzy Grid Partition will enhance the ability in the decision making process. This research will discuss the use of Hesitant Fuzzy Linguistic Term Sets method and Fuzzy Grid Partition for best lecturers determination.

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Konyusheva, O. N. "FUZZY SYSTEMS BASED ON FUZZY LOGIC AND THEIR APPLICATION TO OPTIMIZATION PROBLEMS." SOFT MEASUREMENTS AND COMPUTING 1, no. 2 (2021): 50–64. http://dx.doi.org/10.36871/2618-9976.2021.02.005.

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Currently, fuzzy systems based on fuzzy logic are being implemented in all areas of human activity. The most relevant application of fuzzy set theory is in medicine, environmental protection, disaster protection, education, and many other fields for information processing, diagnostics, evaluation, forecasting, and modeling. This trend exists because of the main feature of fuzzy systems. It consists in the fact that in addition to objective laws, subjective representations and judgments of people play an essential role in their functioning. Almost all concepts in natural language and our knowledge in most areas are fuzzy. The ability of a person to make the right decisions in real situations containing a large number of uncertainties and inaccuracies requires the creation of a mathematical theory that would take into account and model the approximate judgments of a person.

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Yamashita, Toshiyuki. "Fuzzy Logical Approach to Perception of Dot Numerosity." Perceptual and Motor Skills 69, no. 3_suppl (December 1989): 1319–29. http://dx.doi.org/10.2466/pms.1989.69.3f.1319.

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The present study utilized a fuzzy logical approach for understanding human perception or judgments of dot numerosity. In Exp. 1 subjects were required to view dot patterns and to judge the truthfulness of the single and combined statements which asserted that the number of dots was large. The results indicated that (a) the rules based on the minimum and maximum truthfulness of the component statements best approximate subjective conjunction and disjunction about dot numerosity, when subjects kept the operations of the standard logic system in mind, (b) When the subjects based their judgments on perceptive impression, their judgments were best fitted by the multiplicative form.

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Yamashita, Toshiyuki. "Fuzzy Logical Approach to Perception of Dot Numerosity." Perceptual and Motor Skills 69, no. 3-2 (December 1989): 1319–29. http://dx.doi.org/10.1177/00315125890693-247.

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The present study utilized a fuzzy logical approach for understanding human perception or judgments of dot numerosity. In Exp. 1 subjects were required to view dot patterns and to judge the truthfulness of the single and combined statements which asserted that the number of dots was large. The results indicated that (a) the rules based on the minimum and maximum truthfulness of the component statements best approximate subjective conjunction and disjunction about dot numerosity, when subjects kept the operations of the standard logic system in mind. (b) When the subjects based their judgments on perceptive impression, their judgments were best fitted by the multiplicative form.

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Kacprzak, Dariusz. "The Fuzzy SAW Method and Weights Determined Based on Fuzzy Entropy." Przegląd Statystyczny 65, no. 1 (January 30, 2019): 25–40. http://dx.doi.org/10.5604/01.3001.0014.0524.

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The paper presents a new approach to the fuzzy SAW method, which uses fuzzy entropy. It allows to identify the best alternative by the application FSAW method if decision makers use fuzzy numbers or linguistic variables. Moreover, the presented method allows to avoid subjectivity and imprecision caused by incomplete knowledge, judgments, opinions and preferences of decision makers.

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Koll, Mathew, and Padmini Srinivasan. "Fuzzy versus probabilistic models for user relevance judgments." Journal of the American Society for Information Science 41, no. 4 (June 1990): 264–71. http://dx.doi.org/10.1002/(sici)1097-4571(199006)41:4<264::aid-asi5>3.0.co;2-3.

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Fitria Jumarni, Ratih, and Nurnadiah Zamri. "An integration of fuzzy TOPSIS and fuzzy logic for multi-criteria decision making problems." International Journal of Engineering & Technology 7, no. 2.15 (April 6, 2018): 102. http://dx.doi.org/10.14419/ijet.v7i2.15.11362.

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Multi-Criteria Decision Making (MCDM) is a decision-making methods, which it is able to find a unique agreement from number of experts by evaluating the uncertain judgment among them. Several fuzzy logic based approaches have been employed in MCDM to handle the linguistic uncertainties and hesitancy. However, there is still a need to handle high level of uncertainties that exists in decision making problems. Thus, the purpose of this paper is to introduce the new concept namely fuzzy TOPSIS and fuzzy logic based MCDM. The proposed concepts aims to handle the high levels of uncertainties which exists due to the varying experts’ judgments and the vagueness of the appraisal. The proposed method utilized fuzzy logic rule-base in determining the alternatives and criteria for decision matrix. Then, in the aggregation phase, the min operator is used to compute the firing strength for each rule. The feasibility and applicability of the proposed methods are illustrated with an example. This new concept is seen be able to handle intangibles and less cumbersome in mathematical calculations.

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Huseyinov, Ilham, and Feride Savaroglu Tabak. "The Evaluation of Computer Algebra Systems Using Fuzzy Multi-Criteria Decision-Making Models." International Journal of Software Innovation 8, no. 1 (January 2020): 1–16. http://dx.doi.org/10.4018/ijsi.2020010101.

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The main purpose of this study is to present a systematic methodology based on fuzzy Multi-Criteria Decision-Making (FMCDM) models to help users evaluate computer algebra systems (CAS). CAS is a software package for the manipulation of mathematical formulas. The suggested methodology is user-centred which involves users' subjective evaluation judgments. User judgments are represented by means of fuzzy linguistic modelling techniques. An evaluation criteria framework based on the concept of the usefulness of CAS is developed. Next, two FMCDM models – fuzzy Analytical Hierarchy Process (FAHP) and fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) are proposed for the evaluation procedure. The FAHP is applied to determine the relative importance weights of qualitative evaluation criteria; the FTOPSIS is applied to rank the CAS alternatives. The illustrated case study demonstrates the applicability and effectiveness of the proposed methodology.

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NAKAMURA, Kazuo. "Intransitivity of Uncertain Preferential Judgments and Fuzzy Utility Modeling." Transactions of the Society of Instrument and Control Engineers 25, no. 6 (1989): 706–13. http://dx.doi.org/10.9746/sicetr1965.25.706.

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Kumar Goyal, Raman, Jaskirat Singh, Nidhi Kalra, Anshu Parashar, Gagan Singla, and Sakshi Kaushal. "Obtaining Crisp Priorities for Triangular and Trapezoidal Fuzzy Judgments." Computer Systems Science and Engineering 41, no. 1 (2022): 157–70. http://dx.doi.org/10.32604/csse.2022.018962.

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Liu, Yuhong, I.-Ming Jiang, and Meng-I. Tsai. "Influence of Managers’ Subjective Judgments on Project Abandonment Decision Making." International Journal of Information Technology & Decision Making 18, no. 02 (March 2019): 419–43. http://dx.doi.org/10.1142/s0219622018500529.

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Real option valuation with flexibility under uncertainty has been proposed as an alternative and advantageous complement to the traditional net present value (NPV) method for capital budgeting decisions, yet the problem with unrealistic expectations on precision has still not been solved. It appears clearly that a high level of precision in cash flow estimates can be misleading for the decision makers with sentiments. To the extent that precision surrounds a decision, we introduce a fuzzy process into an abandonment option approach, which is built on the use of fuzzy numbers, to investigate the effects of managerial optimism and pessimism when a manager considers whether or not to abandon capital budgeting decisions under imprecision and uncertainty. From the numerical analyses of the proposed model, we find that an optimistic manager tends to continue executing the project, while a pessimistic manager tends to give up the project and liquidate it as the value of the abandonment option is within the range of a fuzzy sentiments interval. In addition, if the project value is below the lower bound of the fuzzy sentiments interval, then it is better to exercise the abandonment option rather than to continue holding it, for both optimistic and pessimistic managers. Finally, this paper also examines why managers may still continue a project, even if its Tobin’s [Formula: see text] value is smaller than one.

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Yager, Ronald R., and Frederick E. Petry. "Crisply Implementing Subjective Fuzzy Requirements." International Journal of Fuzzy System Applications 6, no. 3 (July 2017): 1–5. http://dx.doi.org/10.4018/ijfsa.2017070101.

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In this paper, the authors examine a paradigmatic approach for the implementation of crisp decisions based on imprecise fuzzy requirements residing in the decision maker's cognition in a non-contestable manner. This is closely related to issues of human subjective judgments about such situations. The authors use the airline carry-on bag size decision as paradigm example for the discussions.

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Bolton, Amy E., Randolph S. Astwood, and Gwendolyn E. Campbell. "Policy Capturing and Fuzzy Logic: A Better Approach to Representing Judgment Data?" Proceedings of the Human Factors and Ergonomics Society Annual Meeting 46, no. 3 (September 2002): 541–45. http://dx.doi.org/10.1177/154193120204600368.

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At the 45th annual meeting of HFES, we conducted an alternative format session in which fuzzy logic was introduced as an alternative approach to analyzing judgment data and representing decision-making policies (see Buff et al., 2001). During the alternative format session, usability judgments were collected on-site for Advanced Distance Learning (ADL) applications. These data provided the basis for an empirical assessment of the value added of one modeling technique, fuzzy logic, over the more traditional approach to analyzing policy capturing data, multiple linear regression. This paper describes the results of an empirical assessment of the two modeling techniques. For a discussion of the empirical results of the impact of the different usability dimensions on the learning effectiveness of ADL applications, see Holness, Pharmer, and Buff (2002).

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Sidik, Galih Kurniawan, and Taufik Djatna. "A FAIRNESS MODEL BASED ON INTERVAL TYPE-2 FUZZY SET FOR ISLAMIC FINANCING SCORING IN INDONESIA." Airlangga International Journal of Islamic Economics and Finance 1, no. 1 (November 12, 2018): 43. http://dx.doi.org/10.20473/aijief.v1i1.10431.

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Conventional credit scoring model could lead to serious and unfair problems because in certain case it would incriminate one party in financing. Islamic financing scoring model complies with Sharia rules and ensures fairness among parties. Currently, there are no certain rules on Islamic financing scoring model which lead to subjective judgments. In the subjective judgments, words could mean different things to different people. Thus, this paper proposed and deployed models for scoring of default risk level by using Interval Type-2 Fuzzy Set model to support the subjective judgments in maintaining Sharia rules. Installment amount and the sum of delay period has used as variables for that scoring. Interval Type-2 Fuzzy Set model was proposed to support the subjective judgments in maintaining Sharia rules. Beginning delay period also used as a weight to the risk scoring results. Besides that, this paper also proposed the method for computing real loss value. It has used as a basis for fines computation according to default risk level, bad debt expense, and installment weighted average.

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Takayanagi, Sumiko, and Norman Cliff. "An Examination of Graduate Students' Statistical Judgments: Statistical and Fuzzy Set Approaches." Psychological Reports 86, no. 1 (February 2000): 243–59. http://dx.doi.org/10.2466/pr0.2000.86.1.243.

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The present study examined how statistical significance levels are treated and interpreted by graduate students who use hypothesis-testing in their scientific investigation. To test underlying psychological aspects of hypothesis-testing, the idea of fuzzy set theory was employed to identify the uncertain points in judgments. 34 graduate students in a psychology department made judgments about hypothetical statistical decisions. The results indicated that (1) the majority of these students treated significance levels on a continuum and rated them according to the magnitude of statistical significance; (2) the subjects shifted their decisions based on the types of hypothetical scenarios but not by the sample sizes; instead, they interpreted a smaller sample size as being less reliable. (3) The subjects frequently chose formally used statistical terms, e.g., Significant and Not Significant, more than graduated verbal expressions, e.g., Marginally Significant and Borderline Significant; and (4) the Fuzziness (degree of confidence in decision-making) was dependent on individuals and existed more in the critical points of transition where judgments are most difficult. The Fuzziness Index illustrated the subtle shifts of human decision-making patterns in statistical judgments. Underlying decision uncertainties and difficulties can be illustrated by functions generated from fuzzy set theory, which may more closely resemble human psychological mechanism. This integrative study of fuzzy set theory and behavioral measurements appears to provide a technique that is more natural for examining and understanding imprecise boundaries of human decisions.

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Nakamura, Kazuo. "Canonical fuzzy numbers of dimension two and fuzzy utility difference for understanding preferential judgments." Information Sciences 50, no. 1 (February 1990): 1–22. http://dx.doi.org/10.1016/0020-0255(90)90002-r.

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Ocampo, Lanndon, Eppie Clark, and Kae Vines Tanudtanud. "A Sustainable Manufacturing Strategy from Different Strategic Responses under Uncertainty." Journal of Industrial Engineering 2015 (February 10, 2015): 1–11. http://dx.doi.org/10.1155/2015/210568.

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This paper presents a decision framework that highlights the integration of manufacturing strategy (MS) and sustainability along with strategic responses as a significant component. This integration raises complexity and uncertainty in decision-making following the number of subjective components with their inherent relationships that must be brought into context and the huge amount of required information in eliciting judgments. Thus, a proposed hybrid multicriteria decision-making (MCDM) approach in the form of an integrated probabilistic fuzzy analytic network process (PROFUZANP) is adopted in this work. In this method, analytic network process (ANP) serves as the main framework in identifying policy options of manufacturing strategy. Fuzzy set theory (FST) is used to describe vagueness in decision-making which is carried out by eliciting judgments in pairwise comparisons using linguistic variables with corresponding triangular fuzzy numbers (TFNs). Probability theory is used to handle randomness in aggregating judgments of multiple decision-makers. Results show that a stakeholder-oriented approach is considered the most relevant strategic response in developing a sustainable manufacturing strategy. The contribution of this work lies in identifying the policies which constitute a sustainable manufacturing strategy using an integrated MCDM approach under uncertainty.

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Wardoyo, Retantyo, and Tenia Wahyuningrum. "University Website Quality Ranking using Logarithmic Fuzzy Preference Programming." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 5 (October 1, 2018): 3349. http://dx.doi.org/10.11591/ijece.v8i5.pp3349-3358.

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The current tight competition in developing University websites forces developers to create better products that meet users needs and convinient. There are at least two factors representing university websites; accessibility and usability. We test three criteria of accessibility and usability that are called stickiness, backlink, and web page loading time. Usability and accessibility are closely related to subjective user judgments. Human judgment cannot be valid. Thus the use of fuzzy numbers are expected to provide solutions in calculating the results. In this research, the question of usability is a multi criteria decision-making problem that is caused by its complex structure. We use the Logarithmic Fuzzy Preference Programming (LFPP) method, which is a refinement of the Fuzzy Analytical Hierarchy Process method, to solve this problem. This research aims to re- assess the rank of five Indonesian university websites. Based on LFPP method, we obtain that the equation of model gets high consistency of the set priority matching to fuzzy pairwise comparison matrix of three selection criteria. The calculation results show that stickiness is the most significant factor that affects the quality of the websites.

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Sudakov, V., and T. Sivakova. "Methodology for processing expert judgments based on fuzzy weighted summation." IOP Conference Series: Materials Science and Engineering 927 (September 26, 2020): 012041. http://dx.doi.org/10.1088/1757-899x/927/1/012041.

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MIKHAILOV, LUDMIL, HOSEIN DIDEHKHANI, and SOHEIL SADI-NEZHAD. "WEIGHTED PRIORITIZATION MODELS IN THE FUZZY ANALYTIC HIERARCHY PROCESS." International Journal of Information Technology & Decision Making 10, no. 04 (July 2011): 681–94. http://dx.doi.org/10.1142/s0219622011004518.

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The paper deals with the group prioritization problem in the fuzzy analytic hierarchy process. We extend the fuzzy preference programming method to fuzzy group prioritization by introducing important weights of decision-makers (DMs). The modified prioritization problem is represented as a weighted fuzzy goal programming model. Additionally, we represent the uncertain DMs' importance weights as fuzzy numbers and modify the goal programming model by a possibilistic approach. Both proposed models transform the initial prioritization problems with fuzzy or crisp important weights into equivalent crisp linear programs. Unlike the known fuzzy prioritization methods, the proposed approach does not require an additional defuzzification procedure for final ranking of alternatives and can deal with incomplete set of comparison judgments.

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Zhao, Zhi, and Zhuo Nan Feng. "Fuzzy Decision Theory Applications in the Field of Oil and Gas Production and Operation." Advanced Materials Research 1044-1045 (October 2014): 1859–62. http://dx.doi.org/10.4028/www.scientific.net/amr.1044-1045.1859.

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This article in view of the oil and gas production and operation plan evaluation indexes both depend on each other, and contradictory, difficult to conduct a comprehensive evaluation of characteristics. Using the fuzzy mathematics method to establish calculation model, through the fuzzy comprehensive evaluation, selected from several schemes out a best solution, to help managers to make right decisions and judgments.

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Han, Dan, Guang Yu Wang, and Tian Yang Zang. "Application of Fuzzy Decision Theory in the Oil-Gas Field Production and Management." Applied Mechanics and Materials 488-489 (January 2014): 1297–300. http://dx.doi.org/10.4028/www.scientific.net/amm.488-489.1297.

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For evaluation indicators are dependent on each other and contradictory, difficult to conduct a comprehensive evaluation in the oil-gas production management program, the paper uses the fuzzy mathematics method to establish calculation model, selects out a best solution from a number of programs to help field managers to make the right decisions and judgments by the fuzzy comprehensive evaluation.

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Chen, Yuan, Bing Li, and Xiao Jun Yang. "An Integrated Fuzzy Multi-Attribute Decision-Making Methodology for Evaluation of Mechanical Product." Key Engineering Materials 450 (November 2010): 534–38. http://dx.doi.org/10.4028/www.scientific.net/kem.450.534.

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The concept evaluation of mechanical product is essentially a multi-attribute decision making (MADM) problem in the fuzzy environment. In order to reduce the adverse impact of preference or judgments of decision makers on the final evaluation results, this paper attempts to propose an integrated fuzzy multi-attribute decision making methodology that combines the fuzzy TOPSIS technique and the objective weighting to evaluate mechanical product. The fuzzy TOPSIS technique is applied to rank the design alternatives, and the objective weighting method is integrated into the fuzzy TOPSIS technique to determine the appropriate criteria weights. Finally, a real application to pan mechanism selection for a cooking robot is demonstrated.

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Chen, Dingjun, Shaoquan Ni, Chang’an Xu, Hongxia Lv, and Keyun Qin. "A Soft Rough-Fuzzy Preference Set-Based Evaluation Method for High-Speed Train Operation Diagrams." Mathematical Problems in Engineering 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/5795604.

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This paper proposes a method of high-speed railway train operation diagram evaluation based on preferences of locomotive operation, track maintenance, S & C, vehicles and other railway departments, and customer preferences. The application of rough set-based attribute reduction obtains the important relative indicators by eliminating excessive and redundant evaluation indicators. Soft fuzzy set theory is introduced for the overall evaluation of train operation diagrams. Each expert utilizes a set of indicators during evaluation based on personal preference. In addition, soft fuzzy set theory is applied to integrate the information obtained via expert evaluation in order to obtain an overall evaluation. The proposed method was validated by a case study. Results demonstrate that the proposed method flexibly expresses the subjective judgments of experts while effectively and reasonably handling the uncertainty of information, which is consistent with the judgment process of humans. The proposed method is also applicable to the evaluation of train operation schemes which consist of multiple diagrams.

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Wu, Hsin-Chieh, Yu-Cheng Wang, and Tin-Chih Toly Chen. "Assessing and Comparing COVID-19 Intervention Strategies Using a Varying Partial Consensus Fuzzy Collaborative Intelligence Approach." Mathematics 8, no. 10 (October 7, 2020): 1725. http://dx.doi.org/10.3390/math8101725.

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The COVID-19 pandemic has severely impacted our daily lives. For tackling the COVID-19 pandemic, various intervention strategies have been adopted by country (or city) governments around the world. However, whether an intervention strategy will be successful, acceptable, and cost-effective or not is still questionable. To address this issue, a varying partial consensus fuzzy collaborative intelligence approach is proposed in this study to assess an intervention strategy. In the varying partial consensus fuzzy collaborative intelligence approach, multiple decision makers express their judgments on the relative priorities of factors critical to an intervention strategy. If decision makers lack an overall consensus, the layered partial consensus approach is applied to aggregate their judgments for each critical factor. The number of decision makers that reach a partial consensus varies from a critical factor to another. Subsequently, the generalized fuzzy weighted assessment approach is proposed to evaluate the overall performance of an intervention strategy for tackling the COVID-19 pandemic. The proposed methodology has been applied to compare 15 existing intervention strategies for tackling the COVID-19 pandemic.

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Moon, Joo Hyun, and Chang Sun Kang. "Use of fuzzy set theory in the aggregation of expert judgments." Annals of Nuclear Energy 26, no. 6 (April 1999): 461–69. http://dx.doi.org/10.1016/s0306-4549(98)00073-5.

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Akbari, Fatemeh, Hamed Fazlollahtabar, and Iraj Mahdavi. "An Uncertain Decision Making Process Considering Customers and Services in Evaluating Banks." International Journal of Strategic Decision Sciences 4, no. 2 (April 2013): 48–78. http://dx.doi.org/10.4018/jsds.2013040104.

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In today’s changing environment two properties are required to service namely good relation with customers and service quality. Nowadays no organization can get great achievement unless it can attract sufficient customers providing better service quality is important for service firms. This paper proposes a novel combined approach utilizing group decision making process to evaluate and rank criteria influencing the customer relationship management and service quality of four banks in Iran based on fuzzy decision making trial and evaluation laboratory (Fuzzy DEMATEL) and fuzzy analytic network process (Fuzzy ANP). Defuzzification of decision makers’ judgments is handled by Converting Fuzzy data into Crisp Scores (CFCS) method. Fuzzy DEMATEL is applied to deal with inner dependencies among criteria. Fuzzy ANP is used to compute final ranking of four banks as an empirical example. An empirical study is presented to illustrate the application of the proposed method.

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Moray, Neville, Eugene Kruschelnicky, Paul Eisen, Laura Money, and I. B. Turksen. "A Fuzzy Set Analysis of Skill, Rule and Knowledge-Based Workload." Proceedings of the Human Factors Society Annual Meeting 32, no. 2 (October 1988): 164–67. http://dx.doi.org/10.1177/154193128803200236.

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Using fuzzy measures of task difficulty the effect of combining different aspects of a task on the overall task workload was explored. A complete set of combination rules is provided, of the general form “if the skill-based component is slightly difficult, the rule-based moderately difficult, and the knowledge-based slightly difficult, then the task as a whole is moderately difficult.” Fuzzy linguistic variables provide an adequate systematic framework for such combined judgments.

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Marimuthu, G., and G. Ramesh. "On Moderate Fuzzy Analytic Hierarchy Process Pairwise Comparison Model With Subcriteria." International Research Journal of Engineering, IT & Scientific Research 2, no. 3 (March 1, 2016): 54. http://dx.doi.org/10.21744/irjeis.v2i3.41.

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Decisions usually involve the getting the best solution, selecting the suitable experiments, most appropriate judgments, taking the quality results etc., using some techniques. Every decision making can be considered as the choice from the set of alternatives based on a set of criteria. The fuzzy analytic hierarchy process is a multi-criteria decision making and is dealing with decision making problems through pairwise comparisons mode [10]. The weight vectors from this comparison model are obtained by using extent analysis method. This paper concern with an alternate method of finding the weight vectors from the original fuzzy AHP decision model (moderate fuzzy AHP model), that has the same rank as obtained in original fuzzy AHP and ideal fuzzy AHP decision models.

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Bai, Libiao, Kaimin Zhang, Huijing Shi, Min An, and Xiao Han. "Project Portfolio Resource Risk Assessment considering Project Interdependency by the Fuzzy Bayesian Network." Complexity 2020 (November 4, 2020): 1–21. http://dx.doi.org/10.1155/2020/5410978.

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Resource risk caused by specific resource sharing or competition among projects due to resource constraints is a major issue in project portfolio management, which challenges the application of risk analysis methods effectively. This paper presents a methodology by using a fuzzy Bayesian network to assess the project portfolio resource risk, determine critical resource risk factors, and propose risk-reduction strategies. In this method, the project portfolio resource risk factors are first identified by taking project interdependency into consideration, and then the Bayesian network model is developed to analyze the risk level of the identified risk factors in which expert judgments and fuzzy set theory are integrated to determine the probabilities of all risk factors to deal with incomplete risk data and information. To reduce the subjectivity of expert judgments, the expert weights are determined by combining experts’ background and reliability degree of expert judgments. A numerical analysis is used to demonstrate the application of the proposed methodology. The results show that project portfolio resource risks can be analyzed effectively and efficiently. Furthermore, “poor communication and cooperation among projects,” “capital difficulty,” and “lack of sharing technology among projects” are considered the leading factors of the project portfolio resource risk. Risk-reduction strategic decisions based on the results of risk assessment can be made, which provide project managers with a useful method or tool to manage project risks.

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WEI, Guiwu. "PICTURE FUZZY CROSS-ENTROPY FOR MULTIPLE ATTRIBUTE DECISION MAKING PROBLEMS." Journal of Business Economics and Management 17, no. 4 (July 8, 2016): 491–502. http://dx.doi.org/10.3846/16111699.2016.1197147.

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In this paper, we investigate the multiple attribute decision making problems with picture fuzzy information. The advantage of picture fuzzy set is easily reflecting the ambiguous nature of subjective judgments because the picture fuzzy sets are suitable for capturing imprecise, uncertain, and inconsistent information in the multiple attribute decision making analysis. Thus, the cross entropy of picture fuzzy sets, called picture fuzzy cross entropy, is proposed as an extension of the cross entropy of fuzzy sets. Then, a multiple attribute decision making method based on the proposed picture fuzzy cross entropy is established in which attribute values for alternatives are picture fuzzy numbers. In decision making process, we utilize the picture fuzzy weighted cross entropy between the ideal alternative and an alternative to rank the alternatives corresponding to the cross entropy values and to select the most desirable one(s). Finally, a practical example for enterprise resource planning system selection is given to verify the developed approach and to demonstrate its practicality and effectiveness.

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Bolturk, Eda, Murat Gülbay, and Cengiz Kahraman. "Sustainable energy selection based on interval-valued intuitionistic fuzzy and neutrosophic aggregation operators." Journal of Intelligent & Fuzzy Systems 39, no. 5 (November 19, 2020): 6553–63. http://dx.doi.org/10.3233/jifs-189118.

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Sustainable energy selection has been a very popular problem among the researchers and various models including deterministic, probabilistic and fuzzy approaches have been developed for the solution of this problem. Fuzzy approaches to sustainable energy selection problems have been often handled in the literature. Aggregation operators for multi-expert decision making problems are an alternative solution technique for multi criteria decision making problems. Since neutrosophic and intuitionistic fuzzy aggregation operators are comparable extensions of ordinary fuzzy sets, they have been employed to aggregate multi-expert judgments. An illustrative energy selection problem is presented, solved by two approaches, and results are compared. The same linguistic data have been used for the comparison purpose.

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Naim, Syibrah, and Hani Hagras. "A Big-Bang Big-Crunch Optimized General Type-2 Fuzzy Logic Approach for Multi-Criteria Group Decision Making." Journal of Artificial Intelligence and Soft Computing Research 3, no. 2 (April 1, 2013): 117–32. http://dx.doi.org/10.2478/jaiscr-2014-0009.

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Abstract Multi-Criteria Group Decision Making (MCGDM) aims to find a unique agreement from a number of decision makers/users by evaluating the uncertainty in judgments. In this paper, we present a General Type-2 Fuzzy Logic based approach for MCGDM (GFLMCGDM). The proposed system aims to handle the high levels of uncertainties which exist due to the varying Decision Makers’ (DMs) judgments and the vagueness of the appraisal. In order to find the optimal parameters of the general type-2 fuzzy sets, we employed the Big Bang-Big Crunch (BB-BC) optimization. The aggregation operation in the proposed method aggregates the various DMs opinions which allow handling the disagreements of DMs’ opinions into a unique approval. We present results from an application for the selection of reading lighting level in an intelligent environment. We carried out various experiments in the intelligent apartment (iSpace) located at the University of Essex. We found that the proposed GFL-MCGDM effectively handle the uncertainties between the various decision makers which resulted in producing outputs which better agreed with the users’ decision compared to type 1 and interval type 2 fuzzy based systems.

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Mishra, Swagatika, Siba Sankar Mahapatra, and Saurav Datta. "Agility evaluation in fuzzy context: influence of decision-makers’ risk bearing attitude." Benchmarking: An International Journal 21, no. 6 (September 30, 2014): 1084–119. http://dx.doi.org/10.1108/bij-04-2012-0026.

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Purpose – The purpose of this paper is to investigate the influence of decision-makers’ (DM) risk bearing attitudes and the effect of the decision-making environment on estimating the overall degree of agility of an organization. The present study explores an extended agility model in a specific organization's hierarchy and reflects how decision-making attitudes alter an organizational agility scenario. Design/methodology/approach – The concept of fuzzy logic has been explored in this paper. Based on DMs’ linguistic judgments, a fuzzy appropriateness rating as well as fuzzy priority weights have been determined for different levels of agile system hierarchy. Using a multi-grade fuzzy approach the overall agility index has been determined. The concept of fuzzy numbers ranking has been explored to show the effect of decision-making attitudes on agility estimations. Findings – Decision-making attributes, e.g. the category of DM (neutral, risk-averse and risk-taking), affect the quantitative evaluation of the overall agility degree, which is correlated with a predefined agility measurement scale. Research limitations/implications – This study explores a triangular fuzzy membership function to express DMs’ linguistic judgments as fuzzy representations. Apart from triangular fuzzy numbers, trapezoidal and Gaussian fuzzy numbers may also be used for agility evaluation. The model may be used in other agile industries for benchmarking and selection of the best approach. Practical implications – Selecting the right decision-making group to compute and analyze the agility level for a particular organization is an important managerial decision. In the case of benchmarking of various agile enterprises the decision-making group bearing the same attitude should be utilized. Originality/value – Agile system modeling and development of agility appraisement platforms have been attempted by previous researchers while the influence of DMs’ risk bearing attitudes, and the effect of the decision-making environment on estimating the overall degree of agility, have rarely been studied. In this context, the authors explore an exhaustive agility model for implementing in a case study and reveal how decision-making attitudes alter organizational agility scenarios.

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Aydoğmuş, Hacer Yumurtacı, Eren Kamber, and Cengiz Kahraman. "ERP selection using picture fuzzy CODAS method." Journal of Intelligent & Fuzzy Systems 40, no. 6 (June 21, 2021): 11363–73. http://dx.doi.org/10.3233/jifs-202564.

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The purpose of this study is to develop an extension of CODAS method using picture fuzzy sets. In this respect, a new methodology is introduced to figure out how picture fuzzy numbers can be applied to CODAS method. COmbinative Distance-based Assessment (CODAS) is a new MCDM method proposed by Ghorabaee et al. Picture fuzzy sets (PFSs) are a new extension of ordinary fuzzy sets for representing human’s judgments having possibility more than two answers such as yes, no, refusal and neutral. Compared with other studies, the proposed method integrates multi-criteria decision analysis with picture fuzzy uncertainty based on Euclidean and Taxicab distances and negative ideal solution. ERP system selection problem is handled as the application area of the developed method, picture fuzzy CODAS. Results indicate that the new proposed method finds meaningful rankings through picture fuzzy sets. Comparative analyzes show that the presented method gives successful and robust results for the solutions of MCDM problems under fuzziness.

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Jamalnia, Aboozar, Hannan Amoozad Mahdiraji, Mohammad Reza Sadeghi, Seyed Hossein Razavi Hajiagha, and Ardalan Feili. "An integrated fuzzy QFD and fuzzy goal programming approach for global facility location-allocation problem." International Journal of Information Technology & Decision Making 13, no. 02 (March 2014): 263–90. http://dx.doi.org/10.1142/s0219622014500400.

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Companies pursuing extension of their activities and new companies in establishment phase are using various concepts and techniques to consider location decision, because location greatly affects both fixed and variable costs and on the overall profit of the company. This paper suggests a new use of quality function deployment (QFD) for facility location selection problem instead of applying it to traditional product quality promotion. Fuzzy sets concept is also incorporated to deal with imprecise nature of the linguistic judgments of decision makers. First, fuzzy QFD as a stand-alone approach is presented to address international facility location selection decision. To consider resource limitations and operational constraints, fuzzy goal programming is combined with fuzzy quality function deployment to present a developed approach to deal with global facility location-allocation decision. A demonstration of the applicability of proposed methodologies in a real-world problem is presented.

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Cao, Huai, Xiao Hui Wang, Fei Yi Mao, and Chong Feng. "Double-Layer Fuzzy Synthetic Evaluation Model of the Colour Comfort Degree in Industrial Circumstance." Advanced Materials Research 591-593 (November 2012): 2540–44. http://dx.doi.org/10.4028/www.scientific.net/amr.591-593.2540.

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The color comfort degree is the fundamental principle of the color design in industrial environment. Based on the fuzzy synthetic evaluation model in fuzzy mathematics, the new model uses analytic hierarchy process to constitute a factor set which will affect the assessing of the colour comfort degree, and analyses the existing research data and applies the grey system theory when the data of some factors are insufficient, to quantify the weight and set up the change curve of the factors. By fuzzy evaluating the comfort degree of each factor with the data on the curve, the new model reduces the subjective judgments in the evaluation model and updates to a more objective and accurate evaluation system-the double-layer fuzzy synthetic evaluation model.

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Nguyen, Hoang. "Fuzzy Methods in Risk Estimation of the Ship System Failures Based on the Expert Judgments." Journal of KONBiN 43, no. 1 (October 1, 2017): 393–403. http://dx.doi.org/10.1515/jok-2017-0058.

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Abstract The paper presents the fuzzy methods in failure modes and effects analysis (FMEA) for estimating the risk of the ship system failures based on the expert judgments. It provides an appropriate representation of the uncertain and ambiguous notions expressed in the natural language. An example of fuzzy intuitionistic FMEA analysis is illustrated in estimating the risk of tanker system failures. The results show that the proposed method in comparison with the traditional FMEA is more effective and useful in estimating the risk of ship system failures based on the expert opinions, available in such cases.

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Oztaysi, Basar, Sezi Cevik Onar, Cengiz Kahraman, and Muharrem Gok. "Call center performance measurement using intuitionistic fuzzy sets." Journal of Enterprise Information Management 33, no. 6 (June 1, 2020): 1647–68. http://dx.doi.org/10.1108/jeim-04-2017-0050.

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PurposeThe companies are struggling to collect invoices due to the decrease in the economic growth. This global trend does not only affect undeveloped countries, but it also has a strong impact on the developed countries. Improving the debt collection process become a significant element to maintain financial stability. The institutions that are specialized on collecting payments, debt collection agencies and their call centers, with their expertise in the field can improve the payment process. Yet, managing evaluating the performance of debt collection agencies is a very hard process that involves uncertainty and imprecision. Performance measurement (PM) is a combination of numerically expressed characteristics which give insight about the success or degree of accomplishment of an activity. PM can be handled in various levels such as individual, team, department or company. The aim of this study is to present a systematic and objective PM method for call centers.Design/methodology/approachIn this study, first an exploratory approach is used to understand the call center measurement problem. Several meetings are done with the representatives of both call center firms and the parent firms that outsource debt collection process. Simultaneously, a broad literature review is conducted. An iterative approach is selected to reach deeper knowledge on the process. New meetings are planned and scope of the literature review has changed based on this iterative approach. After these steps, the problem has been considered as the multi-criteria decision-making problem since more than one criteria should be considered for evaluating the performances of call centers. The result of the literature review and the meetings with experts show that defining the weights for the criteria is very crucial for evaluating the performances accurately. Collecting human judgment for defining the weights of call center criteria necessitates dealing with vagueness and uncertainty. The intuitionistic fuzzy sets excellent tools for representing uncertainty. Interval valued intuitionistic fuzzy sets can easily represent the human judgments. Thus, in this study, an intuitionistic fuzzy multi-criteria decision making approach is used to design the proposed methodology. Incomplete interval-valued intuitionistic preference relations are used to determine the weights of the indicators aggregating linguistic evaluations of the decision makers.FindingsThe proposed approach provides an objective calculation of performance measurement. In order to provide objectivity, indicator performance functions are proposed for the first time in this study. Nine different functions and related parameters are defined to objectively measure indicator performances.Originality/valueThe paper proposes an objective and easy-to-modify approach for call-center PM, which can be used by call center managers. It presents a new fuzzy multi-criteria decision-making (MCDM) method for call center performance evaluation, which can consider the multi-experts' judgments under vagueness and impreciseness, which may be conflicting and incomplete interval-valued intuitionistic fuzzy preference relations. Also nine new functions are defined for indicator performance.

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Wu, Hsin-Chieh, Tin-Chih Toly Chen, Chin-Hau Huang, and Yun-Cian Shih. "Comparing Built-in Power Banks for a Smart Backpack Design Using an Auto-Weighting Fuzzy-Weighted-Intersection FAHP Approach." Mathematics 8, no. 10 (October 13, 2020): 1759. http://dx.doi.org/10.3390/math8101759.

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Smart backpacks are a prevalent application of smart technologies, with functions such as motion recording, navigation, and energy harvesting and provision. Selecting a suitable built-in power bank is a critical task for a smart backpack design, which has rarely been investigated in the past. To fulfill this task, an auto-weighting fuzzy-weighted-intersection fuzzy analytic hierarchy process (FAHP) approach is proposed in this study. When decision makers lack an overall consensus, the auto-weighting fuzzy-weighted-intersection FAHP approach specifies decision makers’ authority levels according to the consistency ratios of their judgments. In this way, the consensus among all decision makers can be sought. The auto-weighting fuzzy-weighted-intersection FAHP approach has been applied to compare six mobile power banks for a smart backpack design.

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Sakawa, Masatoshi, and Kosuke Kato. "An Interactive Fuzzy Satisficing Method for Multiobjective Nonlinear Integer Programming Problems with Block-Angular Structures through Genetic Algorithms with Decomposition Procedures." Advances in Operations Research 2009 (2009): 1–17. http://dx.doi.org/10.1155/2009/372548.

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We focus on multiobjective nonlinear integer programming problems with block-angular structures which are often seen as a mathematical model of large-scale discrete systems optimization. By considering the vague nature of the decision maker's judgments, fuzzy goals of the decision maker are introduced, and the problem is interpreted as maximizing an overall degree of satisfaction with the multiple fuzzy goals. For deriving a satisficing solution for the decision maker, we develop an interactive fuzzy satisficing method. Realizing the block-angular structures that can be exploited in solving problems, we also propose genetic algorithms with decomposition procedures. Illustrative numerical examples are provided to demonstrate the feasibility and efficiency of the proposed method.

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Jajimoggala, Sarojini, V. V. S. Kesava Rao, and Beela Satyanarayana. "Maintenance Strategy Evaluation Using ANP and Goal Programming." International Journal of Strategic Decision Sciences 2, no. 2 (April 2011): 56–77. http://dx.doi.org/10.4018/jsds.2011040104.

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An optimal maintenance strategy mix is necessary for increasing availability and reliability levels of production facilities without significantly increasing operational costs. The selection of maintenance strategies is a typical Multiple Criteria Decision-Making (MCDM) problem with conflicting goals. Consideration of interdependence among the criteria and alternative policies for maintenance strategy provides valuable cost savings and greater benefits for any hybrid flow systems. For any decision maker, it is convenient to prioritize the criteria of MCDM problems and goals of goal programming problems in fuzzy terms. This paper presents an integrated approach for maintenance policy selection, using fuzzy Analytic Network Process (ANP) within a Goal Programming, based on fuzzy preemptive priority where goal hierarchies are specified in different levels of fuzzy importance. To overcome the criticism of inconsistency, unbalanced scale of judgments and uncertainty in the pair-wise comparison process, criteria weights are determined using modified fuzzy LLSM method.

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Beheshti, H., and M. Alborzi. "Using Fuzzy Logic to Increase the Accuracy of E-Commerce Risk Assessment Based on an Expert System." Engineering, Technology & Applied Science Research 7, no. 6 (December 18, 2017): 2205–9. http://dx.doi.org/10.48084/etasr.1479.

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Strong adaptive control can be exercised even without access to accurate data inputs. Such control is possible through fuzzy mathematics, which is a meta-collection of Boolean logic principles that imply relative accuracy. Fuzzy mathematics find applications in e-commerce, where different risk analysis methods are available for risk assessment and estimation. Such approaches can be quantitative or qualitative, depending on the type of examined data. Quantitative methods are grounded in statistics, whereas qualitative methods are based on expert judgments and fuzzy set theory. Given that qualitative methods are very subjective and deal with vague or inaccurate data, fuzzy logic can be used to extract useful information from data inaccuracies. In this study, a model based on the opinions of e-commerce security experts was designed and implemented by using fuzzy expert systems and MATLAB. A case study was conducted to validate the effectiveness of the Model.

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Yang, Xuan, and Zhou-Jing Wang. "Geometric Least Square Models for Deriving[0,1]-Valued Interval Weights from Interval Fuzzy Preference Relations Based on Multiplicative Transitivity." Mathematical Problems in Engineering 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/180892.

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This paper presents a geometric least square framework for deriving[0,1]-valued interval weights from interval fuzzy preference relations. By analyzing the relationship among[0,1]-valued interval weights, multiplicatively consistent interval judgments, and planes, a geometric least square model is developed to derive a normalized[0,1]-valued interval weight vector from an interval fuzzy preference relation. Based on the difference ratio between two interval fuzzy preference relations, a geometric average difference ratio between one interval fuzzy preference relation and the others is defined and employed to determine the relative importance weights for individual interval fuzzy preference relations. A geometric least square based approach is further put forward for solving group decision making problems. An individual decision numerical example and a group decision making problem with the selection of enterprise resource planning software products are furnished to illustrate the effectiveness and applicability of the proposed models.

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Journal articles on the topic 'Fuzzy judgments'

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