A New Method for Triangular Fuzzy Number Multiple Attribute Decision Making

2006 ◽  
Author(s):  
Qin Juying ◽  
Meng Fanyong ◽  
Zeng Xuelan
Keyword(s):  
Decision Making ◽  
Fuzzy Number ◽  
Multiple Attribute Decision Making ◽  
Triangular Fuzzy Number ◽  
New Method ◽  
Multiple Attribute

scholarly journals Relative Similarity Programming Model for Uncertain Multiple Attribute Decision-Making Objects and Its Application

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Zhili Huang ◽  
Qinglan Chen ◽  
Liu Chen ◽  
Qinyuan Liu
Keyword(s):  
Decision Making ◽  
Fuzzy Number ◽  
Programming Model ◽  
Weight Vector ◽  
Multiple Attribute Decision Making ◽  
Triangular Fuzzy Number ◽  
Similarity Degree ◽  
Multiple Attribute ◽  
Model Algorithm ◽  
Relative Similarity

This paper is concerned with the uncertain multiattribute decision-making (UMADM) of which the attribute value is triangular fuzzy number. Firstly, the max-relative similarity degree and min-relative similarity degree of alternative decision-making objects are given based on the relative similarity degree of triangular fuzzy number, the advantage relation theories to comparative relative similarity degree of triangular fuzzy number are proposed, and some good properties, relations, and conclusions are derived. Secondly, in order to determine the attribute weight vector, a triangular fuzzy number-based decision-making object relative similarity programming model is established with the help of maximizing possibility degree algorithm rules in the cooperative game theory. Subsequently, by aggregating the comparison overall relative similarity degree values of all decision-making objects, we could pick over and sort the set of alternative objects and gather a new model algorithm for the relative similarity programming of triangular fuzzy number-based multiple attribute decision-making alternatives. Finally, an example is given to illustrate the feasibility and practicability of the model algorithm presented in this paper.

scholarly journals Generalized Linguistic Hesitant Intuitionistic Fuzzy Hybrid Aggregation Operators

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Wei Yang ◽  
Jiarong Shi ◽  
Yongfeng Pang
Keyword(s):  
Decision Making ◽  
Geometric Mean ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
New Method ◽  
Weighted Averaging ◽  
Fuzzy Information ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Special Cases

Some hybrid aggregation operators have been developed based on linguistic hesitant intuitionistic fuzzy information. The generalized linguistic hesitant intuitionistic fuzzy hybrid weighted averaging (GLHIFHWA) operator and the generalized linguistic hesitant intuitionistic fuzzy hybrid geometric mean (GLHIFHGM) operator are defined. Some special cases of the new aggregation operators are studied and many existing aggregation operators are special cases of the new operators. A new multiple attribute decision making method based on the new aggregation operators is proposed and a practical numerical example is presented to illustrate the feasibility and practical advantages of the new method.

Model for Software Quality Evaluation with Fuzzy Information

2016 ◽  
Vol 13 (10) ◽  
pp. 7394-7398
Author(s):  
Yi-Ding Zhao ◽  
Zhi-Min Li ◽  
Xi-Guang Zhang
Keyword(s):  
Decision Making ◽  
Relative Entropy ◽  
Software Quality ◽  
Quality Evaluation ◽  
Multiple Attribute Decision Making ◽  
Triangular Fuzzy Number ◽  
Ideal Solution ◽  
Software Quality Evaluation ◽  
Relative Closeness ◽  
Multiple Attribute

To study the problem of multiple attribute decision making in which the decision making information values are triangular fuzzy number, a relative entropy decision making method for software quality evaluation is proposed. Then, according to the concept of the relative entropy, the relative closeness degree is defined to determine the ranking order of all alternatives by calculating the relative entropy to both the fuzzy positive-ideal solution (FPIS) and fuzzy negative-ideal solution (FNIS) simultaneously. At last, a numerical example for software quality evaluation is provided to illustrate the proposed method. The result shows the approach is simple, effective and easy to calculate.

Human Immunodeficiency Virus (HIV) infection model based on triangular neutrosophic cubic hesitant fuzzy number

2019 ◽  
Vol 12 (05) ◽  
pp. 1950055 ◽  
Author(s):  
Fazli Amin ◽  
Aliya Fahmi
Keyword(s):  
Decision Making ◽  
Human Immunodeficiency Virus ◽  
Fuzzy Number ◽  
Score Function ◽  
Multiple Attribute Decision Making ◽  
Infection Model ◽  
Weighted Arithmetic ◽  
Multiple Attribute ◽  
Immunodeficiency Virus ◽  
Hiv Infection Model

In this paper, we define the basic concept of triangular neutrosophic cubic hesitant fuzzy number and their properties. We develop a triangular neutrosophic cubic hesitant fuzzy ordered weighted arithmetic averaging (TNCHFOWAA) operator and a triangular neutrosophic cubic hesitant fuzzy ordered weighted geometric averaging (TNCHFOWGA) operator to aggregate triangular neutrosophic cubic hesitant fuzzy number (TNCHFN) information and investigate their properties. Furthermore, a multiple attribute decision-making method based on the TNCHFOWAA operator and triangular neutrosophic cubic hesitant fuzzy ordered weighted geometric (TNCHFOWG) operator and the score function of TNCHFN is established under a TNCHFN environment. Finally, an illustrative example of investment alternatives is given to demonstrate the application and effectiveness of the developed approach.

Method for Two-People Multiple-Attribute Decision Making and its Application

2011 ◽  
Vol 204-210 ◽  
pp. 2061-2064
Author(s):  
Fang Wei Zhang ◽  
Shi He Xu ◽  
Bao Shi
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Evidence Theory ◽  
Multiple Attribute Decision Making ◽  
New Method ◽  
Multiple Attribute

In this paper we study the multi-attribute group decision-making problems and put forward a kind of method. In this method, based on clustering evidence theory, the decision-making information is translated into evidences to support different decision-making program. Then, by the amount of evidences, decision-making program ranking is completed. The method’s character can not only rank the decision-making programs by their merits, but also give each program the probability to be the best. Finally, an example is given to show the rationality and effectiveness of the new method.

scholarly journals Multiple-Attribute Decision-Making Problem Using TOPSIS and Choquet Integral with Hesitant Fuzzy Number Information

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Harish Garg ◽  
Abazar Keikha ◽  
Hassan Mishmast Nehi
Keyword(s):  
Decision Making ◽  
Fuzzy Number ◽  
Choquet Integral ◽  
Multiple Attribute Decision Making ◽  
Hesitant Fuzzy Set ◽  
Fuzzy Information ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Collection Data ◽  
Topsis Technique

The paper aims are to present a method to solve the multiple-attribute decision-making (MADM) problems under the hesitant fuzzy set environment. In MADM problems, the information collection, aggregation, and the measure phases are crucial to direct the problem. However, to handle the uncertainties in the collection data, a hesitant fuzzy number is one of the most prominent ways to express uncertain and vague information in terms of different discrete numbers rather than a single crisp number. Additionally, to aggregate and to rank the collective numbers, a TOPSIS (“Technique for Order of Preference by Similarity to Ideal Solution”) and the Choquet integral (CI) are the useful tools. Keeping all these features, in the present paper, we combine the TOPSIS and CI methods for hesitant fuzzy information and hence present a method named as TOPSIS-CI to address the MADM problems. The presented method has been described with a numerical example. Finally, the validity of the stated method as well as a comparative analysis with the existing methods is addressed in detail.

Supplier Selection Using Combined Comparing Interval Grey Numbers and Dominance-Based Rough Sets

2011 ◽  
Vol 186 ◽  
pp. 601-605
Author(s):  
Li Ping Huang ◽  
Jin Jin Li
Keyword(s):  
Decision Making ◽  
Probability Distribution ◽  
Rough Sets ◽  
Supplier Selection ◽  
Multiple Attribute Decision Making ◽  
Selection Problem ◽  
New Method ◽  
Multiple Attribute ◽  
Supplier Selection Problem

Supplier selection is a MADM problem. In this paper, a new method to deal with the supplier selection problem is proposed. The work procedure is as follows: firstly, perfects the method of comparing grey numbers with their probability distribution. Secondly, applies the method of multiple attribute decision making based on dominance-base rough sets to the supplier selection problem. Finally, an example of supplier selection problem is used to illustrate the proposed approach.

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