scholarly journals Intuitionistic Fuzzy (IF) Overlap Functions and IF-Rough Sets with Applications

Symmetry ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1494
Author(s):  
Xiaofeng Wen ◽  
Xiaohong Zhang ◽  
Tao Lei
Keyword(s):  
Decision Making ◽  
Rough Set ◽  
Fuzzy Topsis ◽  
Theoretical Research ◽  
New Class ◽  
Intuitionistic Fuzzy ◽  
Generating Method ◽  
Multi Attribute Decision Making ◽  
Intuitionistic Fuzzy Topsis ◽  
First Time

Overlap function (which has symmetry and continuity) is widely used in image processing, data classification, and multi-attribute decision making problems. In recent years, theoretical research on overlap function has been extended to interval valued overlap function and lattice valued overlap function, but intuitionistic fuzzy overlap function (IF-overlap function) has not been studied. In this paper, the concept of IF-overlap function is proposed for the first time, then the generating method of IF-overlap function is given. The representable IF-overlap function is defined, and the concrete examples of representable and unrepresentable IF-overlap functions are given. Moreover, a new class of intuitionistic fuzzy rough set (IF-roght set) model is proposed by using IF-overlap function and its residual implication, which extends the IF-rough set model based on intuitionistic fuzzy triangular norm, and the basic properties of the new intuitionistic fuzzy upper and lower approximate operators are analyzed and studied. At the same time, the established IF-rough set based on IF-overlap function is applied to MCDM (multi-criteria decision-making) problems, the intuitionistic fuzzy TOPSIS method is improved. Through the comparative analysis of some cases, the new method is proved to be flexible and effective.

Selecting a CNC Machine Tool Using the Intuitionistic Fuzzy TOPSIS Approach for FMC

2013 ◽  
Vol 315 ◽  
pp. 196-205 ◽  
Author(s):  
Nguyen Huu Tho ◽  
Siti Zawiah Md Dawal ◽  
Nukman Yusoff ◽  
Farzad Tahriri ◽  
Hideki Aoyama
Keyword(s):  
Decision Making ◽  
Machine Tool ◽  
Fuzzy Topsis ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Tool Selection ◽  
Machine Tool Selection ◽  
Intuitionistic Fuzzy ◽  
Topsis Approach ◽  
Intuitionistic Fuzzy Topsis

Decision making for machine tool selection is intractable work of managers due to the factors involving the vague and imprecise information. The degree of hesitation is considered in the experts judgment. In this paper, an integration of the intuitionistic fuzzy (IF) Entropy and TOPSIS method are utilized to solve the vague information for decision-making process in machine tool selection. In particular, the weights of criteria are calculated by the IF Entropy and the TOPSIS is employed to determine the priority of alternative. The results of the numerical example show this integration is practical and easy to use for engineers and managers in the companies.

scholarly journals Evaluating Projects Based on Intuitionistic Fuzzy Group Decision Making

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Babak Daneshvar Rouyendegh
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Topsis ◽  
Project Selection ◽  
Weighted Averaging ◽  
Intuitionistic Fuzzy ◽  
Actual Application ◽  
Intuitionistic Fuzzy Topsis ◽  
Fuzzy Group Decision Making

There are various methods regarding project selection in different fields. This paper deals with an actual application of construction project selection, using two aggregation operators. First, the opinion of experts is used in a model of group decision making called intuitionistic fuzzy TOPSIS (IFT). Secondly, project evaluation is formulated by dynamic intuitionistic fuzzy weighted averaging (DIFWA). Intuitionistic fuzzy weighted averaging (IFWA) operator is utilized to aggregate individual opinions of decision makers (DMs) for rating the importance of criteria and alternatives. A numerical example for project selection is given to clarify the main developed result in this paper.

scholarly journals Covering-Based Spherical Fuzzy Rough Set Model Hybrid with TOPSIS for Multi-Attribute Decision-Making

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 547 ◽  
Author(s):  
Shouzhen Zeng ◽  
Azmat Hussain ◽  
Tahir Mahmood ◽  
Muhammad Irfan Ali ◽  
Shahzaib Ashraf ◽  
...  
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Rough Set ◽  
Real Life ◽  
Intuitionistic Fuzzy Sets ◽  
Fuzzy Rough Set ◽  
Intuitionistic Fuzzy ◽  
Multi Attribute Decision Making ◽  
Topsis Technique ◽  
Picture Fuzzy Sets

In real life, human opinion cannot be limited to yes or no situations as shown in an ordinary fuzzy sets and intuitionistic fuzzy sets but it may be yes, abstain, no, and refusal as treated in Picture fuzzy sets or in Spherical fuzzy (SF) sets. In this article, we developed a comprehensive model to tackle decision-making problems, where strong points of view are in the favour; neutral; and against some projects, entities, or plans. Therefore, a new approach of covering-based spherical fuzzy rough set (CSFRS) models by means of spherical fuzzy β -neighborhoods (SF β -neighborhoods) is adopted to hybrid spherical fuzzy sets with notions of covering the rough set. Then, by using the principle of TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) to present the spherical fuzzy, the TOPSIS approach is presented through CSFRS models by means of SF β -neighborhoods. Via the SF-TOPSIS methodology, a multi-attribute decision-making problem is developed in an SF environment. This model has stronger capabilities than intuitionistic fuzzy sets and picture fuzzy sets to manage the vague and uncertainty. Finally, the proposed method is demonstrated through an example of how the proposed method helps us in decision-making problems.

A decision making model for selecting start-up businesses in a government venture capital scheme

2016 ◽  
Vol 54 (3) ◽  
Author(s):  
Eric Afful-Dadzie ◽  
Anthony Afful-Dadzie
Keyword(s):  
Decision Making ◽  
Venture Capital ◽  
Fuzzy Topsis ◽  
Topsis Method ◽  
Intuitionistic Fuzzy ◽  
Start Up ◽  
Start Ups ◽  
Intuitionistic Fuzzy Topsis ◽  
Practical Implications ◽  
Selection Of

Purpose The paper proposes an intuitionistic fuzzy TOPSIS multi-criteria decision making (MCDM) method for the selection of start-up businesses in a government venture capital (GVC) scheme. Most GVC funded start-ups fail or underperform compared to those funded by private venture capitals due to a number of reasons including lack of transparency and unfairness in the selection process. By its design, the proposed method is able to increase transparency and reduce the influence of bias in GVC start-up selection processes. The proposed method also models uncertainty in the selection criteria using fuzzy set theory that mirrors the natural human decision making process. Design/methodology/approach The proposed method first presents a set of criteria relevant to the selection of early stage but high potential start-ups in a Government Venture Capital (GVC) financing scheme. These criteria are then analyzed using the TOPSIS method in an intuitionistic fuzzy environment. The intuitionistic Fuzzy Weighted Averaging (IFWA) Operator is used to aggregate ratings of decision makers. A numerical example of how the proposed method could be used in GVC start-up candidates’ selection in a highly competitive government venture capital scheme is provided. Findings The methodology adopted increases fairness and transparency in the selection of start-up businesses for fund support in a government-run venture capital scheme. The criteria set proposed is ideal for selecting start-up businesses in a government controlled venture capital scheme. The decision making framework demonstrates how uncertainty in the selection criteria are efficiently modelled with the TOPSIS method. Practical implications As government venture capital schemes increase around the world, and concerns about failure and underperformance of GVC funded start-ups increase, the proposed method could help bring formalism and ensure the selection of start-ups with high success potential. Originality/value The framework designs relevant sets of criteria for a selection problem, demonstrates the use of extended TOPSIS method in intuitionistic fuzzy sets and apply the proposed method in an area that has not been considered before. Additionally, it demonstrates how intuitionistic fuzzy TOPSIS could be carried out in a real decision making application setting.

scholarly journals An Interval-Valued Intuitionistic Fuzzy TOPSIS Method Based on an Improved Score Function

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Zhi-yong Bai
Keyword(s):  
Decision Making ◽  
Score Function ◽  
Fuzzy Topsis ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Topsis Method ◽  
Intuitionistic Fuzzy ◽  
Relative Closeness ◽  
Intuitionistic Fuzzy Topsis ◽  
Interval Valued

This paper proposes an improved score function for the effective ranking order of interval-valued intuitionistic fuzzy sets (IVIFSs) and an interval-valued intuitionistic fuzzy TOPSIS method based on the score function to solve multicriteria decision-making problems in which all the preference information provided by decision-makers is expressed as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by IVIFS value and the information about criterion weights is known. We apply the proposed score function to calculate the separation measures of each alternative from the positive and negative ideal solutions to determine the relative closeness coefficients. According to the values of the closeness coefficients, the alternatives can be ranked and the most desirable one(s) can be selected in the decision-making process. Finally, two illustrative examples for multicriteria fuzzy decision-making problems of alternatives are used as a demonstration of the applications and the effectiveness of the proposed decision-making method.

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