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.

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.

scholarly journals Decision-Maker’s Risk Preference Based Intuitionistic Fuzzy Multiattribute Decision-Making and Its Application in Robot Enterprises Investment

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Liandong Zhou ◽  
Qifeng Wang
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Weight Vector ◽  
Multiple Attribute Decision Making ◽  
Decision Makers ◽  
Research Papers ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Fuzzy Weight

At present, the utilization of hesitation information of intuitionistic fuzzy numbers is insufficient in many methods which were proposed to solve the intuitionistic fuzzy multiple attribute decision-making problems. And also there exist some flaws in the intuitionistic fuzzy weight vector constructions in many research papers. In order to solve these insufficiencies, this paper defined three construction equations of weight vectors based on the risk preferences of decision-makers. Then we developed an intuitionistic fuzzy dependent hybrid weighted operator (IFDHW) and proposed an intuitionistic fuzzy multiattribute decision-making method. Finally, the effectiveness of this method is verified by a robot manufacturing investment example.

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.

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.

scholarly journals Approaches to Multiple Attribute Decision-Making with Fuzzy Number Intuitionistic Fuzzy Information and Their Application to English Teaching Quality Evaluation

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Zhen Zhang ◽  
Pengfei Su
Keyword(s):  
Decision Making ◽  
Fuzzy Number ◽  
Quality Evaluation ◽  
Teaching Quality ◽  
Multiple Attribute Decision Making ◽  
English Teaching ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Maclaurin Symmetric Mean ◽  
Multiple Attribute

Many experts and scholars focus on the Maclaurin symmetric mean (MSM) operator, which can reflect the interrelationship among the multi-input arguments. It has been generalized to different fuzzy environments and put into use in various actual decision problems. The fuzzy number intuitionistic fuzzy numbers (FNIFNs) could well depict the uncertainties and fuzziness during the English teaching quality evaluation. And the English teaching quality evaluation is frequently viewed as the multiple attribute decision-making (MADM) issue. We expand the MSM equation with FNIFNs to propose the fuzzy number intuitionistic fuzzy MSM (FNIFMSM) equation and fuzzy number intuitionistic fuzzy weighted MSM (FNIFWMSM) equation in this study. A few MADM tools are developed with FNIFWMSM equation. Finally, taking English teaching quality evaluation as an example, this paper illustrates the depicted approach.

scholarly journals Gray Method for Multiple Attribute Decision Making with Incomplete Weight Information under the Pythagorean Fuzzy Setting

2018 ◽  
Vol 29 (1) ◽  
pp. 858-876 ◽  
Author(s):  
Muhammad Sajjad Ali Khan ◽  
Saleem Abdullah ◽  
Peide Lui
Keyword(s):  
Decision Making ◽  
Choquet Integral ◽  
Weight Vector ◽  
Multiple Attribute Decision Making ◽  
Gray Relational Analysis ◽  
Ideal Solution ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
Negative Ideal Solution ◽  
Magdm Problems

Abstract In this study, we developed an approach to investigate multiple attribute group decision-making (MAGDM) problems, in which the attribute values take the form of Pythagorean fuzzy numbers whose information about attribute weights is incompletely known. First, the Pythagorean fuzzy Choquet integral geometric operator is utilized to aggregate the given decision information to obtain the overall preference value of each alternative by experts. In order to obtain the weight vector of the criteria, an optimization model based on the basic ideal of the traditional gray relational analysis method is established, and the calculation steps for solving Pythagorean fuzzy MAGDM problems with incompletely known weight information are given. The degree of gray relation between every alternative and positive-ideal solution and negative-ideal solution is calculated. Then, a relative relational degree is defined to determine the ranking order of all alternatives by calculating the degree of gray relation to both the positive-ideal solution and negative-ideal solution simultaneously. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

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