نتایج جستجو برای: ranking of fuzzy numbers

تعداد نتایج: 21193016  

Chitgar, S. H. Nasseri,

The main aim of this paper is to deal with a fuzzy version of Farkas lemma involving trapezoidal fuzzy numbers. In turns to that the fuzzy linear programming and duality theory on these problems can be used to provide a constructive proof for Farkas lemma. Keywords Farkas Lemma, Fuzzy Linear Programming, Duality, Ranking Functions.

2011
Xiaowei HE Hepu DENG

This paper presents an area-based approach to ranking fuzzy numbers in fuzzy decision making. To ensure that all the information that a fuzzy number has is adequately considered, the concepts of the absolute area and the degree of deviation of a fuzzy number are integrated into the process of comparing and ranking fuzzy numbers. To help the decision maker better address the risk inherent in the...

Journal: :International Journal of Pure and Apllied Mathematics 2016

Journal: :Adv. Fuzzy Systems 2011
P. Phani Bushan Rao N. Ravi Shankar

Ranking fuzzy numbers are an important aspect of decision making in a fuzzy environment. Since their inception in 1965, many authors have proposed different methods for ranking fuzzy numbers. However, there is no method which gives a satisfactory result to all situations. Most of the methods proposed so far are nondiscriminating and counterintuitive. This paper proposes a new method for ranking...

Journal: :Communications of the Korean Mathematical Society 2014

2015
Deng-Feng Li Jie Yang D. F. Li

The order relation of fuzzy number is important in decision making and optimization modeling, and ranking fuzzy numbers is difficult in nature. Ranking trapezoidal intuitionistic fuzzy numbers (TrIFNs) is more difficult due to the fact that the TrIFNs are a generalization of the fuzzy numbers. The aim of this paper is to develop a new methodology for ranking TrIFNs. We define the value-index an...

2011
Tayebeh Hajjari

Since much of human reasoning is based on imprecise, vague and subjective values, most of decision-making processing, in reality, requires handling and evaluation of fuzzy numbers. Zadeh’s (Zadeh 1965) fuzzy logic has given analysts a tool to present the human behavior more precisely, especially where relatively few data exist, and where the expert knowledge about the system is vague and lingui...

Journal: :Journal of Fuzzy Set Valued Analysis 2016

Journal: :International Journal of Fuzzy Logic Systems 2016

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