Combining technique for order preference by similarity to ideal solution with relative preference relation for interval-valued fuzzy multi-criteria decision-making

2019 ◽  
Vol 24 (15) ◽  
pp. 11347-11364 ◽  
Author(s):  
Yu-Jie Wang
Keyword(s):  
Decision Making ◽  
Preference Relation ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Relative Preference ◽  
Order Preference ◽  
Interval Valued

scholarly journals Comparison of the Economic Performance of Turkish Republics in Central Asia with TOPSIS Method

2015 ◽  
Author(s):  
Ziya Gökalp Göktolga ◽  
Engin Karakış ◽  
Hakan Türkay
Keyword(s):  
Decision Making ◽  
Central Asia ◽  
Economic Performance ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Economic Management ◽  
Macroeconomic Indicators ◽  
Order Preference ◽  
Negative Ideal Solution

The aim of this study is to compare the economic performance of Turkish Republics in Central Asia with Multi Criteria Decision Making (MCDM) methods. Turkish Republics have been experiencing a transition from a centrally planned economy towards a market economy since their independence. In this study important macroeconomic indicators are used to determine economic performance. Economic performance evaluation of the country is an important issue for economic management, investors, creditors and stock investors. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method outranks the countries according to the proximity of the positive ideal solution and distance of the negative ideal solution. Economic Performance of Turkish Republics in Central Asia (Azerbaijan, Turkmenistan, Kazakhstan, Kyrgyzstan, and Uzbekistan) are compared with TOPSIS method. İnvestigated with TOPSIS method countries best and worst economic performance years are detected during mentioned period and results are analyzed.

scholarly journals A fuzzy multi-criteria decision-making method for purchasing life insurance in India

2021 ◽  
Vol 10 (1) ◽  
pp. 344-356
Author(s):  
Chinmaya Ranjan Pattnaik ◽  
Sachi Nandan Mohanty ◽  
Sarita Mohanty ◽  
Jyotir Moy Chatterjee ◽  
Biswajit Jana ◽  
...  
Keyword(s):  
Decision Making ◽  
Life Insurance ◽  
Complex Problem ◽  
Insurance Companies ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Insurance Company ◽  
Proposed Model ◽  
Decision Making Problem ◽  
Order Preference

Life insurance is an agreement between an insured and an insurer, where the insurer pays out a sum of money either on a specific period or the death of the insured. Now a day, People can buy a policy through an online platform. There are a lot of insurance companies available in the market, and each company has various policies. Selecting the best insurance company for purchasing an online term plan is a very complex problem. People may confuse to choose the best insurance company for buying an online term. It is a multi-criteria decision making (MCDM) problem, and the problem consists of different criteria and various alternatives. Here in this paper, a model has been proposed to solve this decision-making problem. In this model, a fuzzy multi-criteria decision-making approach combined with technique for order preference by similarity to ideal solution (TOPSIS) and it has been applied to rank the different insurance companies based on online term plans. The experimental results show that the life insurance corporation of India (LIC) gets the top rank out of 12 companies for purchasing an online term plan. A sensitivity analysis has been performed to validate the proposed model.

ELECTRE Method Based on Interval-Valued Intuitionistic Fuzzy Number

2012 ◽  
Vol 220-223 ◽  
pp. 2308-2312 ◽  
Author(s):  
Jun Li ◽  
Min Lin ◽  
Jian Hua Chen
Keyword(s):  
Decision Making ◽  
Fuzzy Number ◽  
Preference Relation ◽  
Intuitionistic Fuzzy Set ◽  
Multi Criteria Decision Making ◽  
Intuitionistic Fuzzy Number ◽  
Intuitionistic Fuzzy ◽  
Electre Method ◽  
Deviation Degree ◽  
Interval Valued

A new multi-criteria decision-making method for interval-valued intuitionistic fuzzy number is proposed by the advantage of intuitionistic fuzzy set and ELECTRE method. Firstly, the possibility-degree and deviation-degree of interval number are used to establish the preference relation of interval-valued intuitionistic fuzzy number. Then, we exposit the decision theory and the steps of this method. Finally, a numerical example is given to illustrate the application of the method. The numerical results show that it is feasible and effective.

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.

Identification of User Preference for Multi-Criteria Reporting in Business Intelligence

2018 ◽  
pp. 16-47
Author(s):  
Martin Aruldoss ◽  
Miranda Lakshmi Travis ◽  
Prasanna Venkatesan Venkatasamy
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
User Preference ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Order Preference ◽  
Banking Business ◽  
Different Levels ◽  
Support Decision Making

Business intelligence (BI) is an integrated set of tools used to support the transformation of data into information in order to support decision making. Among different functionalities, reporting plays a significant role that provides information to its readers to make better decisions. BI lacks user-specific reporting to the different levels of users of an organization. Different users require different kinds of reporting with respect to different requirement (criteria) in an organization. A multi-criteria reporting (MCR) finds the suitable information to suitable user based on the multiple conflicting preferences of a user. Technique for order preference by similarity to ideal solution (TOPSIS) is the most popularly applied multi-criteria decision-making (MCDM) technique selected to identify different levels of user preference for MCR. Banking business is considered as a case study to identify user preference for MCR. This research also designs evaluation metrics for TOPSIS.

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