scholarly journals Interval Data Aggregation Technology for Large Scale Decision Making

2021 ◽  
Author(s):  
Linxin Chen ◽  
Riqing Chen ◽  
Jian Lin
Keyword(s):  
Decision Making ◽  
Large Scale ◽  
Score Function ◽  
Weighted Averaging ◽  
Accuracy Function ◽  
Interval Numbers ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Interval Valued

Abstract In this paper, an improved multiple attribute decision making (MADM) method based on the proposed novel score function and accuracy function of interval-valued intuitionistic fuzzy numbers (IVIFNs) is proposed to aggregate large-scale data. The attribute values in the decision matrices provided by each decision-maker (DM), which are characterized by interval numbers. First, a transformation matrix is introduced to define the concepts of satisfactory set, un- satisfactory set and uncertainty set of alternatives. An approach is then developed for aggregating attribute values into IVIFNs, and we will obtain the collective evaluation of each alternative. Next, using the interval-valued intuitionistic fuzzy weighted averaging operator, the collective attribute values characterized by IVIFNs are aggregated to get the overall evaluation of alternatives. The score function and accuracy function are applied to calculate the score degree and the rank of each alternative. Finally, a large-scale example is given to verify the validity of the reported method.

MAGDM Problems with Correlation Coefficient of Triangular Fuzzy IFS

2017 ◽  
pp. 154-192
Author(s):  
John Robinson P. ◽  
Henry Amirtharaj E. C.
Keyword(s):  
Decision Making ◽  
Correlation Coefficient ◽  
Fuzzy Set ◽  
Intuitionistic Fuzzy Set ◽  
Weighted Averaging ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Decision Making Models ◽  
Magdm Problems ◽  
Interval Valued

Correlation coefficient of Intuitionistic Fuzzy Set (IFS), Interval valued IFS, Triangular IFS and Trapezoidal IFS are already present in the literature. This paper proposes the correlation coefficient for Triangular Fuzzy Intuitionistic Fuzzy set (TrFIFS). The method on uncertain Multiple Attribute Group Decision Making (MAGDM) problems based on aggregating intuitionistic fuzzy information is investigated for TrFIFSs. The Triangular Fuzzy Intuitionistic Fuzzy Ordered Weighted Averaging (TrFIFOWA) operator is proposed for TrFIFSs and the Triangular Fuzzy Intuitionistic Fuzzy Ordered Weighted Geometric (TrFIFOWG) operator is utilized for decision making models where expert weights are completely unknown. Based on these operators and the correlation coefficient defined for the TrFIFSs, new decision making models are proposed with numerical illustrations. Some comparisons are also made with existing ranking methods for validity.

scholarly journals Algorithms Based on COPRAS and Aggregation Operators with New Information Measures for Possibility Intuitionistic Fuzzy Soft Decision-Making

2020 ◽  
Vol 2020 ◽  
pp. 1-20 ◽  
Author(s):  
Harish Garg ◽  
Rishu Arora
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Score Function ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Soft Decision ◽  
Information Measures ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute

The objective of this paper is to present novel algorithms for solving the multiple attribute decision-making problems under the possibility intuitionistic fuzzy soft set (PIFSS) information. The prominent characteristics of the PIFSS are that it considers the membership and nonmembership degrees of each object during evaluation and their corresponding possibility degree. Keeping these features, this paper presents some new operation laws, score function, and comparison laws between the pairs of the PIFSSs. Further, we define COmplex PRoportional ASsessment (COPRAS) and weighted averaging and geometric aggregation operators to aggregate the PIFSS information into a single one. Later, we develop two algorithms based on COPRAS and aggregation operators to solve decision-making problems. In these approaches, the experts and the weights of the parameters are determined with the help of entropy and the distance measure to remove the ambiguity in the information. Finally, a numerical example is given to demonstrate the presented approaches.

scholarly journals A Heterogeneous MCDM Framework for Sustainable Supplier Evaluation and Selection Based on the IVIF-TODIM Method

2019 ◽  
Vol 11 (18) ◽  
pp. 5057 ◽  
Author(s):  
Ren-Jie Mao ◽  
Jian-Xin You ◽  
Chun-Yan Duan ◽  
Lu-Ning Shao
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Third Party ◽  
Multi Criteria Decision Making ◽  
Interval Numbers ◽  
Intuitionistic Fuzzy Numbers ◽  
Sustainability Performance ◽  
Intuitionistic Fuzzy ◽  
Relative Closeness ◽  
Interval Valued

The third-party platform named ECO system is used by many transnational companies to monitor the sustainability performance of their global suppliers because of its easiness and shareability. Nonetheless, methods used in this platform for evaluating and calculating the sustainability performance of the alternative suppliers are criticized for their lack of accuracy. In response to these problems, this paper presents a heterogeneous multi-criteria decision-making (MCDM) method based on interval-valued intuitionistic fuzzy--an acronym in Portuguese for interactive multi-criteria decision making (IVIF--TODIM) to improve the efficiency of the evaluation model. Considering the varying features of evaluation criteria, i.e., either quantitative or qualitative, the evaluation values under different criteria are expressed in their appropriate information types. In this paper, a general method based on the relative closeness to the technique for order preference by similarity to ideal solution (TOPSIS) method is applied for aggregating the heterogeneous assessment information, including crisp numbers, interval numbers, and triangular fuzzy numbers (TFNs), into interval-valued intuitionistic fuzzy numbers (IVIFNs). Then, the TODIM (an acronym in Portuguese for interactive multi-criteria decision making) is extended and employed to prioritize the alternative suppliers. Finally, the applicability and effectiveness of the proposed method is verified by a practical example of polymer manufacturing company and a comparison analysis with existing methods.

PROJECTION MODELS FOR INTUITIONISTIC FUZZY MULTIPLE ATTRIBUTE DECISION MAKING

2010 ◽  
Vol 09 (02) ◽  
pp. 267-280 ◽  
Author(s):  
ZESHUI XU ◽  
HUI HU
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Ideal Point ◽  
Multiple Attribute Decision Making ◽  
Included Angle ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Fuzzy Ideal ◽  
Interval Valued

The aim of this paper is to investigate the intuitionistic fuzzy multiple attribute decision-making problems where the attribute values are expressed in intuitionistic fuzzy numbers or interval-valued intuitionistic fuzzy numbers. We introduce some notions, such as intuitionistic fuzzy ideal point, interval-valued intuitionistic fuzzy ideal point, the modules of intuitionistic fuzzy numbers, and interval-valued intuitionistic fuzzy numbers. We also introduce the cosine of the included angle between the attribute value vectors of each alternative and the intuitionistic fuzzy ideal point, and the cosine of the included angle between the attribute value vectors of each alternative and the interval-valued intuitionistic fuzzy ideal point. Then we establish two projection models to measure the similarity degrees between each alternative and the intuitionistic fuzzy ideal point, and between each alternative and the interval-valued intuitionistic fuzzy ideal point. Based on the projection models, we can rank the given alternatives and then select the most desirable one. Finally, we illustrate the developed projection models with a numerical example.

scholarly journals AN APPROACH FOR MADM PROBLEMS WITH INTERVAL-VALUED INTUITIONISTIC FUZZY SETS BASED ON NONLINEAR FUNCTIONS

2015 ◽  
Vol 22 (3) ◽  
pp. 336-356 ◽  
Author(s):  
Jian WU ◽  
Qingwei CAO ◽  
Hui LI
Keyword(s):  
Score Function ◽  
Multiple Attribute Decision Making ◽  
Nonlinear Functions ◽  
Intuitionistic Fuzzy Numbers ◽  
Attribute Weights ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Fuzzy Madm ◽  
Optimized Model ◽  
Interval Valued

This paper investigates an approach for multiple attribute decision making (MADM) problems with interval-valued intuitionistic fuzzy numbers (IVIFNs). To do that, the nonlinear score, accuracy and hesitation functions of IVIFNs are developed based on the normal distribution. The novelty of these nonlinear functions is that they have an additional variance value, which can have more information to rank IVIFNs than Xu and Chen’s score function and Ye’s accuracy function. Based on these nonlinear functions, a ranking method for IVIFNs is proposed. Furthermore, a nonlinearly optimized model is proposed to obtain attribute weights by integrating these nonlinear functions. Then, we develop an approach for interval-valued intuitionistic fuzzy MADM programs in which two cases are considered: the attribute weight information is known and particularly known. In the end, we apply the proposed approach to select green supplier.

scholarly journals Some Generalized Dependent Aggregation Operators with Interval-Valued Intuitionistic Fuzzy Information and Their Application to Exploitation Investment Evaluation

2013 ◽  
Vol 2013 ◽  
pp. 1-24 ◽  
Author(s):  
Xiao-wen Qi ◽  
Chang-yong Liang ◽  
Junling Zhang
Keyword(s):  
Aggregation Operators ◽  
Weighted Averaging ◽  
Weighting Method ◽  
Intuitionistic Fuzzy Numbers ◽  
Investment Evaluation ◽  
Ordered Weighted Averaging ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Wide Range ◽  
Interval Valued

We investigate multiple attribute group decision making (MAGDM) problems with arguments taking the form of interval-valued intuitionistic fuzzy numbers. In order to relieve influence of unfair arguments, a Gaussian distribution-based argument-dependent weighting method and a hybrid support-function-based argument-dependent weighting method are devised by, respectively, measuring support degrees of arguments indirectly and directly, based on which the Gaussian generalized interval-valued intuitionistic fuzzy ordered weighted averaging operator (Gaussian-GIIFOWA) and geometric operator (Gaussian-GIIFOWG), the power generalized interval-valued intuitionistic fuzzy ordered weighted averaging (P-GIIFOWA) operator and geometric (P-GIIFOWA) operator are proposed to generalize a wide range of aggregation operators for decision makers to flexibly choose in decision modelling. And some desirable properties of the proposed operators are also analyzed. Further, application of an approach integrating proposed operators to exploitation investment evaluation of tourist spots has shown the effectiveness and practicality of developed methods; experimental results also verify the properties of proposed operators.

SOME CONTINUOUS AGGREGATION OPERATORS WITH INTERVAL-VALUED INTUITIONISTIC FUZZY INFORMATION AND THEIR APPLICATION TO DECISION MAKING

2012 ◽  
Vol 20 (02) ◽  
pp. 185-209 ◽  
Author(s):  
JIAN LIN ◽  
QIANG ZHANG
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Fuzzy Information ◽  
Numerical Examples ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Interval Valued

In this paper, some new operators for aggregating interval-valued intuitionistic fuzzy information are proposed to deal with multiple attribute decision making problems. Firstly, the C-IFOWA operator and C-IFOWG operator are developed to aggregate all the values in the interval-valued intuitionistic fuzzy numbers. Some of their desirable properties are also studied. Secondly, in order to aggregate a set of interval-valued intuitionistic fuzzy numbers, some new aggregation operators are proposed based on the C-IFOWA operator and C-IFOWG operator. Thirdly, two methods for multiple attribute decision making, in which the attribute values are given in the forms of interval-valued intuitionistic fuzzy numbers are presented. Finally, two numerical examples are provided to illustrate the practicality and validity of the proposed methods.

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