Multi–criteria decision making towards housemaids using single valued neutrosophic fuzzy numbers and comparing with triangular neutrosophic fuzzy number

2020 ◽  
Author(s):  
N. Lakshmipathy ◽  
A. Rajkumar ◽  
S. Shalini ◽  
Chirag Goyal
Keyword(s):  
Decision Making ◽  
Fuzzy Number ◽  
Fuzzy Numbers ◽  
Multi Criteria Decision Making

scholarly journals Generalization and ranking of fuzzy numbers by relative preference relation

2021 ◽  
Author(s):  
Kavitha Koppula ◽  
Babushri Srinivas Kedukodi ◽  
Syam Prasad Kuncham
Keyword(s):  
Decision Making ◽  
Fuzzy Number ◽  
Fuzzy Numbers ◽  
Preference Relation ◽  
Multi Criteria Decision Making ◽  
Fuzzy Preference Relation ◽  
Trapezoidal Fuzzy Numbers ◽  
Relative Preference ◽  
Decision Making Model ◽  
Ranking Of Fuzzy Numbers

AbstractWe define $$2n+1$$ 2 n + 1 and 2n fuzzy numbers, which generalize triangular and trapezoidal fuzzy numbers, respectively. Then, we extend the fuzzy preference relation and relative preference relation to rank $$2n+1$$ 2 n + 1 and 2n fuzzy numbers. When the data is representable in terms of $$2n+1$$ 2 n + 1 fuzzy number, we generalize the FMCDM (fuzzy multi-criteria decision making) model constructed with TOPSIS and relative preference relation. Lastly, we give an example from telecommunications to present the proposed FMCDM model and validate the results obtained.

scholarly journals Disjunctive Representation of Triangular Bipolar Neutrosophic Numbers, De-Bipolarization Technique and Application in Multi-Criteria Decision-Making Problems

Symmetry ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 932 ◽  
Author(s):  
Avishek Chakraborty ◽  
Sankar Prasad Mondal ◽  
Shariful Alam ◽  
Ali Ahmadian ◽  
Norazak Senu ◽  
...  
Keyword(s):  
Decision Making ◽  
Real Number ◽  
Fuzzy Number ◽  
Fuzzy Numbers ◽  
Research Paper ◽  
Frame Of Reference ◽  
Multi Criteria Decision Making ◽  
Membership Functions ◽  
Decision Making Problem ◽  
Neutrosophic Number

This research paper adds to the theory of the generalized neutrosophic number from a distinctive frame of reference. It is universally known that the concept of a neutrosophic number is generally associated with and strongly related to the concept of positive, indeterminacy and non-belongingness membership functions. Currently, all membership functions always lie within the range of 0 to 1. However, we have generated bipolar concept in this paper where the membership contains both positive and negative parts within the range −1 to 0 and 0 to 1. We describe different structures of generalized triangular bipolar neutrosophic numbers, such as category-1, category-2, and category-3, in relation to the membership functions containing dependency or independency with each other. Researchers from different fields always want to observe the co-relationship and interdependence between fuzzy numbers and crisp numbers. In this platform, we also created the perception of de-bipolarization for a triangular bipolar rneutrosophic number with the help of well-known techniques so that any bipolar neutrosophic fuzzy number of any type can be smoothly converted into a real number instantly. Creating a problem using bipolar neutrosophic perception is a more reliable, accurate, and trustworthy method than others. In this paper, we have also taken into account a multi-criteria decision-making problem (MCDM) for different users in the bipolar neutrosophic domain.

scholarly journals Hexagonal fuzzy approximation of fuzzy numbers and its applications in MCDM

2021 ◽  
Author(s):  
V. Lakshmana Gomathi Nayagam ◽  
Jagadeeswari Murugan
Keyword(s):  
Decision Making ◽  
Fuzzy Number ◽  
Fuzzy Numbers ◽  
Piecewise Linear ◽  
Multi Criteria Decision Making ◽  
Loss Of Information ◽  
Fuzzy Approximation ◽  
Special Cases ◽  
Non Linear ◽  
Intelligent Information

AbstractNumerous research papers and several engineering applications have proved that the fuzzy set theory is an intelligent effective tool to represent complex uncertain information. In fuzzy multi-criteria decision-making (fuzzy MCDM) methods, intelligent information system and fuzzy control-theoretic models, complex qualitative information are extracted from expert’s knowledge as linguistic variables and are modeled by linear/non-linear fuzzy numbers. In numerical computations and experiments, the information/data are fitted by nonlinear functions for better accuracy which may be little hard for further processing to apply in real-life problems. Hence, the study of non-linear fuzzy numbers through triangular and trapezoidal fuzzy numbers is very natural and various researchers have attempted to transform non-linear fuzzy numbers into piecewise linear functions of interval/triangular/trapezoidal in nature by different methods in the past years. But it is noted that the triangular/trapezoidal approximation of nonlinear fuzzy numbers has more loss of information. Therefore, there is a natural need for a better piecewise linear approximation of a given nonlinear fuzzy number without losing much information for better intelligent information modeling. On coincidence, a new notion of Generalized Hexagonal Fuzzy Number has been introduced and its applications on Multi-Criteria Decision-Making problem (MCDM) and Generalized Hexagonal Fully Fuzzy Linear System (GHXFFLS) of equations have been studied by Lakshmana et al. in 2020. Therefore, in this paper, approximation of nonlinear fuzzy numbers into the hexagonal fuzzy numbers which includes trapezoidal, triangular and interval fuzzy numbers as special cases of Hexagonal fuzzy numbers with less loss/gain of information than other existing methods is attempted. Since any fuzzy information is satisfied fully by its modal value/core of that concept, any approximation of that concept is expected to be preserved with same modal value/core. Therefore, in this paper, a stepwise procedure for approximating a non-linear fuzzy number into a new Hexagonal Fuzzy Number that preserves the core of the given fuzzy number is proposed using constrained nonlinear programming model and is illustrated numerically by considering a parabolic fuzzy number. Furthermore, the proposed method is compared for its efficiency on accuracy in terms of loss of information. Finally, some properties of the new hexagonal fuzzy approximation are studied and the applicability of the proposed method is illustrated through the Group MCDM problem using an index matrix (IM).

scholarly journals Trapezoidal Linguistic Cubic Fuzzy TOPSIS Method and Application in a Group Decision Making Program

2019 ◽  
Vol 29 (1) ◽  
pp. 1283-1300 ◽  
Author(s):  
Aliya Fahmi ◽  
Saleem Abdullah ◽  
Fazli Amin ◽  
Muhammad Aslam ◽  
Shah Hussain
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Number ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Hamming Distance ◽  
Fuzzy Topsis ◽  
Multi Criteria Decision Making ◽  
Topsis Method ◽  
Mcdm Method

Abstract The aim of this paper is to define some new operation laws for the trapezoidal linguistic cubic fuzzy number and Hamming distance. Furthermore, we define and use the trapezoidal linguistic cubic fuzzy TOPSIS method to solve the multi criteria decision making (MCDM) method. The new ranking method for trapezoidal linguistic cubic fuzzy numbers (TrLCFNs) are used to rank the alternatives. Finally, an illustrative example is given to verify and prove the practicality and effectiveness of the proposed method.

scholarly journals New Ranking Method For Fuzzy Numbers By Their Expansion Center

2014 ◽  
Vol 4 (3) ◽  
pp. 181-187 ◽  
Author(s):  
Zhenyuan Wang ◽  
Li Zhang-Westmant
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Real Axis ◽  
Fuzzy Number ◽  
Fuzzy Numbers ◽  
Ranking Method ◽  
Important Criterion ◽  
Real Numbers ◽  
Numerical Index ◽  
The Membership Function

Abstract Based on the area between the curve of the membership function of a fuzzy number and the horizontal real axis, a characteristic as a new numerical index, called the expansion center, for fuzzy numbers is proposed. An intuitive and reasonable ranking method for fuzzy numbers based on this characteristic is also established. The new ranking method is applicable for decision making and data analysis in fuzz environments. An important criterion of the goodness for ranking fuzzy numbers, the geometric intuitivity, is also introduced. It guarantees coinciding with the natural ordering of the real numbers.

Contractor Selection Using Integrated Goal Programming and Fuzzy ELECTRE

2014 ◽  
Vol 5 (3) ◽  
pp. 65-86 ◽  
Author(s):  
Ahmad Jafarnejad Chaghooshi ◽  
Ehsan Khanmohammadi ◽  
Maryam Faghei ◽  
Amir Karimi
Keyword(s):  
Decision Making ◽  
Goal Programming ◽  
Fuzzy Numbers ◽  
Multi Criteria Decision Making ◽  
Contractor Selection ◽  
Trapezoidal Fuzzy Numbers ◽  
Technical Capacity ◽  
Selection Of

Outsourcing plays an important role in the success of organizations. One of the risks associated with outsourcing is inappropriate contractor selection which significantly influences the implementation of projects in terms of time, quality, and cost. In this study, we applied multi-criteria decision-making techniques in order to determine the best contractor using criteria such as reputation, offered price, and technical capacity. This study is primarily aimed at identifying important criteria of contractor selection, determining the significance of the criteria, and designing a framework for selection of the most appropriate contractor. Important criteria for selecting contractors were extracted from the literature and experts' views were collected using questionnaire. Accordingly, six criteria were selected and their weights were determined by the application of goal programming. Finally, contractors were ranked and the best contractor was selected using fuzzy ELECTRE technique with trapezoidal fuzzy numbers.

A New Method for Ranking Intuitionistic Fuzzy Numbers

2011 ◽  
Vol 2 (1) ◽  
pp. 43-49 ◽  
Author(s):  
Cui-Ping Wei ◽  
Xijin Tang
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Score Function ◽  
Ranking Method ◽  
New Method ◽  
Multi Criteria Decision Making ◽  
Intuitionistic Fuzzy Numbers ◽  
Additional Information ◽  
Intuitionistic Fuzzy ◽  
Possibility Degree

In this paper the ranking method for intuitionistic fuzzy numbers is studied. The authors first define a possibility degree formula to compare two intuitionistic fuzzy numbers. In comparison with Chen and Tan’s score function, the possibility degree formula provides additional information for the comparison of two intuitionistic fuzzy numbers. Based on the possibility degree formula, the authors give a possibility degree method to rank intuitionistic fuzzy numbers, which is used to rank the alternatives in multi-criteria decision making problems.

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