Parametric computation of a fuzzy set solution to a class of fuzzy linear fractional optimization problems

2016 ◽  
Vol 15 (4) ◽  
pp. 435-455 ◽  
Author(s):  
Bogdana Stanojević ◽  
Milan Stanojević
Keyword(s):  
Fuzzy Set ◽  
Optimization Problems ◽  
Fractional Optimization

Chaotic crow search algorithm for fractional optimization problems

2018 ◽  
Vol 71 ◽  
pp. 1161-1175 ◽  
Author(s):  
Rizk M. Rizk-Allah ◽  
Aboul Ella Hassanien ◽  
Siddhartha Bhattacharyya
Keyword(s):  
Optimization Problems ◽  
Search Algorithm ◽  
Fractional Optimization

scholarly journals Modeling Nonlinear Systems by a Fuzzy Logic Neural Network Using Genetic Algorithms

10.14311/296 ◽  
2001 ◽  
Vol 41 (6) ◽  
Author(s):  
Abdel-Fattah Attia ◽  
P. Horáček
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Membership Function ◽  
Fuzzy Set ◽  
Optimization Problems ◽  
Optimization Method ◽  
Fuzzy Approach ◽  
Gaussian Shape ◽  
Neuro Fuzzy ◽  
Definition Of

The main aim of this work is to optimize the parameters of the constrained membership function of the Fuzzy Logic Neural Network (FLNN). The constraints may be an indirect definition of the search ranges for every membership shape forming parameter based on 2nd order fuzzy set specifications. A particular method widely applicable in solving global optimization problems is introduced. This approach uses a Linear Adapted Genetic Algorithm (LAGA) to optimize the FLNN parameters. In this paper the derivation of a 2nd order fuzzy set is performed for a membership function of Gaussian shape, which is assumed for the neuro-fuzzy approach. The explanation of the optimization method is presented in detail on the basis of two examples.

Interval Methods and Fuzzy Optimization

1997 ◽  
Vol 05 (03) ◽  
pp. 239-249 ◽  
Author(s):  
Weldon A. Lodwick ◽  
K. David Jamison
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Interval Analysis ◽  
Fuzzy Set Theory ◽  
Fuzzy Numbers ◽  
Optimization Problems ◽  
Fuzzy Optimization ◽  
Interval Methods

In this paper, we describe interval-based methods for solving constrained fuzzy optimization problems. The class of fuzzy functions we consider for the optimization problems is the set of real-valued functions where one or more parameters/coefficients are fuzzy numbers. The focus of this research is to explore some relationships between fuzzy set theory and interval analysis as it relates to optimization problems.

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