Multicriteria optimization based on neural network, fuzzy and neuro-fuzzy approximation of decision maker's utility function

Authors:
A. P. Karpenko;D. A. Moor;D. T. Mukhlisullina
Affiliations:
Bauman Moscow State Technical University, Moscow, Russian Federation 105005;Bauman Moscow State Technical University, Moscow, Russian Federation 105005;Bauman Moscow State Technical University, Moscow, Russian Federation 105005
Venue:
Optical Memory and Neural Networks
Year:
2012

Citing 2
Cited 1

Comparison of Multiobjective Evolutionary Algorithms: Empirical Results

Evolutionary Computation
Multicriteria optimization based on neural network approximation of decision maker's utility function

Optical Memory and Neural Networks

Nonuniform covering method as applied to multicriteria optimization problems with guaranteed accuracy

Computational Mathematics and Mathematical Physics

Quantified Score

Hi-index	0.00

Visualization

Abstract

A direct adaptive method of multicriteria optimization based on neural network, fuzzy and neuro-fuzzy approximation of the decision maker's utility function is introduced. A comparative analysis of efficiency of the various approximation techniques for solving two-and three-criterion optimization test problems is carried out.