Models for MADM with hesitant interval-valued fuzzy information under uncertain environment

2021 ◽  
Vol 25 (3) ◽  
pp. 315-322
Author(s):  
Hongjun Wang
Keyword(s):  
Fuzzy Set ◽  
Mathematic Model ◽  
Fuzzy Information ◽  
Uncertain Environment ◽  
Numerical Example ◽  
New Algorithms ◽  
Interval Valued

This paper is a research of interval-valued fuzzy and Muirhead Mean algorithms. We deduced new algorithms named as hesitant interval-valued fuzzy Muirhead Mean (HIVFMM) and hesitant interval-valued fuzzy Muirhead Mean (HIVFWMM) with Muirhead Mean algorithms based on Hesitant interval-valued fuzzy set (HIVFS). Firstly, we introduced some concepts and operation laws of HIVFS and the formula form of MM, then we combined them both and gave the proof process of properties and theorems, a mathematic model applying to MADM and a numerical example was given to illustrate the effectively and practically.

Interval-Valued Dual Hesitant Fuzzy Heronian Mean Aggregation Operators and their Application to Multi-Attribute Decision Making

2018 ◽  
Vol 17 (01) ◽  
pp. 1850005 ◽  
Author(s):  
Yuqi Zang ◽  
Xiaodong Zhao ◽  
Shiyong Li
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Aggregation Operators ◽  
Hesitant Fuzzy Set ◽  
Fuzzy Information ◽  
New Approach ◽  
Dual Hesitant Fuzzy Set ◽  
Multi Attribute Decision Making ◽  
Interval Valued ◽  
Heronian Mean

The interval-valued dual hesitant fuzzy set (IVDHFS) can depict the imprecise, vague and indeterminate information and Heronian mean (HM) has the prominent characteristic of capturing the correlation of the aggregated arguments. In this paper, we investigate multi-attribute decision making (MADM) problems based on HM, in which the attribute values are assumed in the form of interval-valued dual hesitant fuzzy information. Firstly, we briefly present some concepts of IVDHFS and HM. Then, we propose the interval-valued dual hesitant fuzzy Heronian mean (IVDHFHM) operator and the interval-valued dual hesitant fuzzy geometric Heronian mean (IVDHFGHM) operator. We also prove that they satisfy some desirable properties. Further, we consider the importance of the input arguments and derive the interval-valued dual hesitant fuzzy weighted Heronian mean (IVDHFWHM) operator and the interval-valued dual hesitant fuzzy weighted geometric Heronian mean (IVDHFWGHM) operator, and then develop the procedure of MADM. Finally, an illustrate example is given to demonstrate the practicality and effectiveness of the new approach.

An improved fuzzy TODIM method based on entropy measure under Intuitionistic Fuzzy Information

2021 ◽  
Vol 23 (05) ◽  
pp. 464-470
Author(s):  
Sunit Kumar ◽  
◽  
Satish Kumar ◽  
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Intuitionistic Fuzzy Set ◽  
Score Function ◽  
Entropy Measure ◽  
Multi Criteria Decision Making ◽  
Fuzzy Information ◽  
Numerical Example ◽  
Intuitionistic Fuzzy ◽  
Todim Method

Intuitionistic fuzzy set (IFS) is one of the most extensive and important tool to accommodate more uncertainties than existing fuzzy set structures. In the present paper, we describe an improved entropy based on TODIM procedure for handling multi-criteria decision-making (MCDM) under IF setting and also the weight information is partially known. First, we study the basic notions and operating laws of IFSs, also the accuracy and score function of it. The new entropy has been proposed. Secondly, the IF information-based decision-making technique for MCDM is presented. Lastly, a numerical example is given related, to demonstrate that their results are credible and feasible.

Rule Extraction Based on Interval-Valued Rough Fuzzy Sets

2014 ◽  
Vol 665 ◽  
pp. 668-673
Author(s):  
Hua Ni Qin ◽  
Da Rong Luo
Keyword(s):  
Knowledge Discovery ◽  
Rough Set ◽  
Fuzzy Set ◽  
Fuzzy Numbers ◽  
Fuzzy Information ◽  
Modified Model ◽  
Sorting Method ◽  
Rough Fuzzy Set ◽  
General Sorting ◽  
Interval Valued

A model of interval-valued rough fuzzy set combining interval-valued fuzzy set and rough set is investigated in this paper. Firstly, considering the deficiency of general sorting method between any interval-valued fuzzy numbers, an improved sorting method and a pair of new approximation operators about minimum and maximum are presented. Based on the improved operators, a model of interval-valued rough fuzzy set is established. At last, by using the modified model of interval-valued rough fuzzy set, a method of knowledge discovery in interval-valued fuzzy information systems is investigated.

scholarly journals Interval-Valued Pythagorean Hesitant Fuzzy Set and Its Application to Multiattribute Group Decision-Making

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-26
Author(s):  
Maoyin Zhang ◽  
Tingting Zheng ◽  
Wanrong Zheng ◽  
Ligang Zhou
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Set ◽  
Group Decision ◽  
Score Function ◽  
Hesitant Fuzzy Set ◽  
Fuzzy Information ◽  
Interval Numbers ◽  
Operational Laws ◽  
Interval Valued

Pythagorean hesitant fuzzy sets are widely watched because of their excellent ability to deal with uncertainty, imprecise and vague information. This paper extends Pythagorean hesitant fuzzy environments to interval-valued Pythagorean hesitant fuzzy environments and proposes the concept of interval-valued Pythagorean hesitant fuzzy set (IVPHFS), which allows the membership of each object to be a set of several pairs of possible interval-valued Pythagorean fuzzy elements. Furthermore, we develop a series of aggregation operators for interval-valued Pythagorean hesitant fuzzy information and apply them to multiattribute group decision-making (MAGDM) problems. Then, some desired operational laws and properties of IVPHFSs are studied. Especially, considering an interval-valued Pythagorean fuzzy element (IVPHFE) is formed by several pairs of interval values, this paper proposes the concepts of score function and accuracy function in the form of two interval numbers which can retain interval-valued Pythagorean fuzzy information as much as possible. Then, the relationship among these operators is discussed by comparing the interval numbers. Eventually, an illustrative example fully shows the feasibility, practicality, and effectiveness of the proposed approach.

scholarly journals New Operators of Cubic Picture Fuzzy Information with Applications

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Tehreem ◽  
Abdu Gumaei ◽  
Amjad Hussain
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Aggregation Operators ◽  
Fuzzy Information ◽  
Picture Fuzzy Set ◽  
Decision Making Problem ◽  
Picture Fuzzy Sets ◽  
Interval Valued

The researcher has been facing problems while handling imprecise and vague information, i.e., the problems of networking, decision-making, etc. For encountering such complicated data, the notion of fuzzy sets (FS) has been considered an influential tool. The notion was extended to its generalizations by a number of researchers in different ways which helps to understand and assess even more complex issues. This article characterizes imprecision with four kinds of values of membership. In this work, we aim to define and examine cubic picture fuzzy sets and give an application on averaging aggregation operators. We first introduce the notion of a cubic picture fuzzy set, which is a pair of interval-valued picture fuzzy set and a picture fuzzy set by giving examples. Then, we define two kinds of ordering on these sets and also discuss some set-theoretical properties. Moreover, we introduce three kinds of averaging aggregation operators based on cubic picture fuzzy sets and, at the end, we illustrate the results with a decision-making problem by using one of the provided aggregation operators.

Interval-Valued Intuitionistic Multiplicative Sets

2014 ◽  
Vol 22 (03) ◽  
pp. 385-406 ◽  
Author(s):  
Yuan Jiang ◽  
Zeshui Xu ◽  
Jiuping Xu
Keyword(s):  
Fuzzy Set ◽  
Intuitionistic Fuzzy Set ◽  
Basic Component ◽  
Distance Measures ◽  
Weighted Distance ◽  
Numerical Example ◽  
Intuitionistic Fuzzy ◽  
The Difference ◽  
Interval Valued

A generalization of the notion of intuitionistic multiplicative set (IMS) is given in this paper, which is called interval-valued intuitionistic multiplicative set (IVIMS). The IVIMS uses an unsymmetrical scale (Saaty's 1-9 scale) instead of the ordinary symmetrical scale in an intuitionistic fuzzy set or an interval-valued intuitionistic fuzzy set. IVIMSs can reflect our intuition more objectively in some special situations. The basic component of an IVIMS is interval-valued intuitionistic multiplicative number (IVIMN). To rank IVIMNs, the comparison laws are developed. Based on the pseudo-multiplication, we explore some interval-valued intuitionistic multiplicative operations and obtain several specific results when some specific forms are assigned. In addition, some distance measures and weighted distance measures between IVIMSs are developed to describe the difference of any two IVIMSs. By analyzing the range of the uncertain degree, a generalized interval-valued intuitionistic multiplicative set is presented, which is a generalization of the notions of IMS and IVIMS. Finally, a numerical example is given to illustrate our results.

scholarly journals Interval-Valued Intuitionistic Hesitant Fuzzy Aggregation Operators and Their Application in Group Decision-Making

2013 ◽  
Vol 2013 ◽  
pp. 1-33 ◽  
Author(s):  
Zhiming Zhang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Set ◽  
Group Decision ◽  
Aggregation Operators ◽  
Hesitant Fuzzy Set ◽  
Mathematical Tool ◽  
Fuzzy Information ◽  
Intuitionistic Fuzzy ◽  
Interval Valued

Hesitant fuzzy sets, permitting the membership of an element to be a set of several possible values, can be used as an efficient mathematical tool for modelling people’s hesitancy in daily life. In this paper, we extend the hesitant fuzzy set to interval-valued intuitionistic fuzzy environments and propose the concept of interval-valued intuitionistic hesitant fuzzy set, which allows the membership of an element to be a set of several possible interval-valued intuitionistic fuzzy numbers. The aim of this paper is to develop a series of aggregation operators for interval-valued intuitionistic hesitant fuzzy information. Then, some desired properties of the developed operators are studied, and the relationships among these operators are discussed. Furthermore, we apply these aggregation operators to develop an approach to multiple attribute group decision-making with interval-valued intuitionistic hesitant fuzzy information. Finally, a numerical example is provided to illustrate the application of the developed approach.

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