Interval valued intuitionistic fuzzy soft multi set theoretic approach to decision making problems

Mukherjee, Anjan; Das, Ajoy Kanti

doi:10.1109/ic4.2015.7375640

Cited by 4 publications

(4 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Feng [22] presented the use of level soft sets in decision-making in view of fuzzy soft sets. Later on, more broad properties and applications of soft set theory have been examined by Maji, Feng and others, for instance, see [ [15], [21], [23], [29], [34], [42], [44]]. Correspondingly, fuzzy soft comprehensively connected [ [16], [26], [38]].…”

Section: Introductionmentioning

confidence: 99%

“…Recently, Mukherjee and Das [31] called attention to that Alkhazaleh-Salleh technique [3] is not adequate to understand FSM-set based decision-making issues and they acquainted another algorithm with FSM-set based decision-making issues using Feng's algorithm [22]. Also, some other articles were committed to this point, for instance [ [32], [34], [35], [36]].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Einstein-operations on fuzzy soft multi sets and decision making

Mukherjee

Das²

2022

bspm

Self Cite

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Einstein-operations on fuzzy soft multi sets and decision making

Mukherjee

Das²

2022

bspm

Self Cite

View full text Add to dashboard Cite

show abstract

“…Combining soft sets [15] with fuzzy sets [21] and intuitionistic fuzzy sets [2], Maji et al [9][10][11][12] defined fuzzy soft sets and intuitionistic fuzzy soft sets, which are rich potential for solving decision making problems. By using these definitions, the uses of soft set theory have been concentrated progressively (see [4], [5], [7], [8], [14], [16], [17], [19], [20]). Zhu [23] characterized t-norm and t-conorm products of fuzzy parameterized fuzzy soft sets and presented its application in decision-making.…”

Section: Introductionmentioning

confidence: 99%

Investment decision-making based on an intuitionistic fuzzy soft set

Mukherjee¹,

Das²,

Saha³

2016

Journal of Fuzzy Set Valued Analysis

Self Cite

View full text Add to dashboard Cite

Research on soft set and decision-making have been developed rapidly since it can be applied easily to several areas like computer science, information technology, medical science, economics, environments, engineering, among other. Making decisions on investment is certainly the most important task of an investor and it is often a very difficult one. In this research work, we characterize t-norm and t-conorm products on the intuitionistic fuzzy approximate value sets (briefly, IFAV-sets) of an intuitionistic fuzzy soft set (briefly, IFS-set) and applying these products, we introduce an adjustable investment model based on an IFS-set, for investment decision in an uncertain situation. The feasibility of our proposed IFS-set based investment model in practical application is shown by some examples and also, we show the effect of non-membership degrees of elements on decision making.

show abstract

“…Also, new distance measures under IVIF context have attracted authors that provide effective GDM process [14,15]. Mukherjee and Das [16,17] developed a theoretic framework of IVIF soft sets and effectively solved investor selection problem. The fusing of IVIF judgment matrix is an interesting research topic which has attracted researchers to contribute with some novel mechanisms [18,19].…”

Section: Introductionmentioning

confidence: 99%

A Scientific Decision Framework for Supplier Selection under Interval Valued Intuitionistic Fuzzy Environment

Krishankumar

Ravichandran

Ramprakash

2017

Mathematical Problems in Engineering

View full text Add to dashboard Cite

This paper proposes a new scientific decision framework (SDF) under interval valued intuitionistic fuzzy (IVIF) environment for supplier selection (SS). The framework consists of two phases, where, in the first phase, criteria weights are estimated in a sensible manner using newly proposed IVIF based statistical variance (SV) method and, in the second phase, the suitable supplier is selected using ELECTRE (ELimination and Choice Expressing REality) ranking method under IVIF environment. This method involves three categories of outranking, namely, strong, moderate, and weak. Previous studies on ELECTRE ranking reveal that scholars have only used two categories of outranking, namely, strong and weak, in the formulation of IVIF based ELECTRE, which eventually aggravates fuzziness and vagueness in decision making process due to the potential loss of information. Motivated by this challenge, third outranking category, called moderate, is proposed, which considerably reduces the loss of information by improving checks to the concordance and discordance matrices. Thus, in this paper, IVIF-ELECTRE (IVIFE) method is presented and popular TOPSIS method is integrated with IVIFE for obtaining a linear ranking. Finally, the practicality of the proposed framework is demonstrated using SS example and the strength of proposed SDF is realized by comparing the framework with other similar methods.

show abstract

Interval valued intuitionistic fuzzy soft multi set theoretic approach to decision making problems

Cited by 4 publications

References 15 publications

Einstein-operations on fuzzy soft multi sets and decision making

Einstein-operations on fuzzy soft multi sets and decision making

Investment decision-making based on an intuitionistic fuzzy soft set

A Scientific Decision Framework for Supplier Selection under Interval Valued Intuitionistic Fuzzy Environment

Contact Info

Product

Resources

About