Fuzzy Decision Making in Politics: A Linguistic Fuzzy-Set Approach (LFSA)

2005 ◽  
Vol 13 (1) ◽  
pp. 23-56 ◽  
Author(s):  
Badredine Arfi
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Multiple Criteria ◽  
Decision Makers ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Trust And Power

In this article I use linguistic fuzzy-set theory to analyze the process of decision making in politics. I first introduce a number of relevant elements of (numerical and linguistic) fuzzy-set theory that are needed to understand the terminology as well as to grasp the scope and depth of the approach. I then explicate a linguistic fuzzy-set approach (LFSA) to the process of decision making under conditions in which the decision makers are required to simultaneously satisfy multiple criteria. The LFSA approach is illustrated through a running (hypothetical) example of a situation in which state leaders need to decide how to combine trust and power to make a choice on security alignment.

scholarly journals Fuzzy Insurance

1990 ◽  
Vol 20 (1) ◽  
pp. 33-55 ◽  
Author(s):  
Jean Lemaire
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Fuzzy Set ◽  
Life Insurance ◽  
Fuzzy Set Theory ◽  
Fuzzy Numbers ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Basic Concepts ◽  
Definition Of

AbstractFuzzy set theory is a recently developed field of mathematics, that introduces sets of objects whose boundaries are not sharply defined. Whereas in ordinary Boolean algebra an element is either contained or not contained in a given set, in fuzzy set theory the transition between membership and non-membership is gradual. The theory aims at modelizing situations described in vague or imprecise terms, or situations that are too complex or ill-defined to be analysed by conventional methods. This paper aims at presenting the basic concepts of the theory in an insurance framework. First the basic definitions of fuzzy logic are presented, and applied to provide a flexible definition of a “preferred policyholder” in life insurance. Next, fuzzy decision-making procedures are illustrated by a reinsurance application, and the theory of fuzzy numbers is extended to define fuzzy insurance premiums.

A Fuzzy Decision-making Approach to Evaluate CO2 Emissions Reduction Policies

2021 ◽  
pp. 097215092110140
Author(s):  
Monika Gupta
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Practical Implication ◽  
Weighted Average ◽  
Road Transport ◽  
Fuzzy Decision Making ◽  
Policy Options ◽  
The Government

The article aims at multi-criteria decision making analysis using the fuzzy set theory to evaluate different policy options to reduce CO2 emissions from road transport in case of India. The fuzzy set theory has been applied to investigate different possible measures which the government can adopt to reduce CO2 emissions and improve air quality. Ordered weighted average operator of linguistic fuzzy set theory is used to rank different policy options. Findings show that the use of low emissions vehicles and the adoption of sustainability-oriented behaviour are considered the most preferred options, which can effectively reduce the CO2 emissions from road transport. The research shows that fuzzy set theory may be an effective tool in analyzing environmental uncertainties. Analyzing the optimal policy measure and prospects of it in different scenarios would help policymakers in designing and focusing on effective policy measures in order to reduce CO2 emissions from road transport in a country like India. The study implies ways to assess policy options for environment management and dealing with climate change. This study also fills the gap between the theoretical fuzzy model and its practical implication in policy decision-making, especially in a sustainability area that is more uncertain.

A fuzzy-set approach for multiple criteria decision making in sustainable consumption of organic food

2021 ◽  
Vol 10 (3) ◽  
pp. 291-300
Author(s):  
Thi Thuy Giang Huynh ◽  
Tien Dung Luu ◽  
Tuan Thanh Phung
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Sustainable Consumption ◽  
Organic Food ◽  
Multiple Criteria ◽  
Government Support ◽  
Income Status ◽  
Aspect Social

The study proposes a set of enablers of the consumer sustainable organic food consumption and detects the interrelationship between these attributes. This paper adopts the fuzzy set theory and decision-making trial and evaluation to explore the interrelationship between attributes, including consumer demographic aspect, psychological aspect, social-level aspect and stakeholder impact being explained through 13 criteria and being assessed by experts in the industry. The findings show that stakeholder impact and demographic aspect belong to a causal group and impact the other two aspects. The six most important attributes affecting sustainable consumption of organic foods are support and guidance from government support, mass media, education and research institutions, educational level, income status and consumer age. The study grants an alternative approach for sustainable consumption theory through providing a fuzzy-set theory for multiple criteria decisions making in sustainable consumption of organic food.

Utilizing Fuzzy Decision Trees in Decision Making

2011 ◽  
pp. 1175-1180
Author(s):  
Malcolm J. Beynon
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Trees ◽  
Decision Rule ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Fuzzy Decision ◽  
Fuzzy Decision Trees ◽  
Rule Systems

The seminal work of Zadeh (1965), fuzzy set theory (FST) has developed into a methodology fundamental to analysis that incorporates vagueness and ambiguity. With respect to the area of data mining, it endeavours to find potentially meaningful patterns from data (Hu & Tzeng, 2003). This includes the construction of if-then decision rule systems, which attempt a level of inherent interpretability to the antecedents and consequents identified for object classification (and prediction), (see Breiman 2001).

Evaluation of Quantified Statements Using Gradual Numbers

2011 ◽  
pp. 246-269 ◽  
Author(s):  
Ludovic Liétard ◽  
Daniel Rocacher
Keyword(s):  
Decision Making ◽  
Expert Systems ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Relational Databases ◽  
Fuzzy Numbers ◽  
Theoretical Background ◽  
Definition Of ◽  
Flexible Querying

This chapter is devoted to the evaluation of quantified statements which can be found in many applications as decision making, expert systems, or flexible querying of relational databases using fuzzy set theory. Its contribution is to introduce the main techniques to evaluate such statements and to propose a new theoretical background for the evaluation of quantified statements of type “Q X are A” and “Q B X are A.” In this context, quantified statements are interpreted using an arithmetic on gradual numbers from Nf, Zf, and Qf. It is shown that the context of fuzzy numbers provides a framework to unify previous approaches and can be the base for the definition of new approaches.

Decision Making Approach using Weighted Coefficient of Correlation along with Generalized Parametric Fuzzy Entropy Measure

2016 ◽  
Vol 5 (3) ◽  
pp. 30-41 ◽  
Author(s):  
Priti Gupta ◽  
Pratiksha Tiwari
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Entropy Measure ◽  
Managerial Decision ◽  
Coefficient Of Correlation ◽  
Different Types ◽  
Segmentation Of Images ◽  
Real World Problems

Decision making involves various attributes along with several decision takers. Recently it has become more complex. This gives raise to uncertainty and associated with the information provided. So it may be appropriate to suggest that uncertainty demonstrates itself in numerous forms and of different types. Uncertainties may arise due to human behaviour, fluctuations of information, unknown facts. Fuzzy set theory is tool to deal with uncertainty in a better way. Both Fuzzy set theory and information theory are involved in dealing with various real-world problems such as segmentation of images, medical diagnosis, managerial decision making etc. Several methods and concepts dealing with imprecision and uncertainty have been proposed by many researchers. In the present communication, the authors have proposed a parametric generalization of entropy introduced by De Luca and Termini along with its basic properties. Further, a new measure of weighted coefficient of correlation is developed and applied to solve decision making problems involving uncertainty.

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