DocumentCode
1277488
Title
Solving constraint satisfaction and optimization problems by a neuro-fuzzy approach
Author
Cavalieri, Salvatore ; Russo, Marco
Author_Institution
Ist. di Inf. e Telecommun., Catania Univ., Italy
Volume
29
Issue
6
fYear
1999
fDate
12/1/1999 12:00:00 AM
Firstpage
895
Lastpage
902
Abstract
The solution of constrained satisfaction and constrained optimization problems using a Hopfield model requires determination of the values of a certain number of coefficients linked to the surrounding conditions of the problem. It is quite difficult to determine these values, mainly because a heuristic search is necessary. This is not only time-consuming but may lead to solutions that are far from optimal, or even nonvalid ones. So far, there have been no works in literature offering a general method for the search for coefficents with will guarantee optimal or close to optimal solutions. This paper proposes a fuzzy approach which allows automatic determination of Hopfield coefficients
Keywords
Hopfield neural nets; constraint theory; fuzzy logic; optimisation; Hopfield coefficients; Hopfield model; coefficients; constrained optimization problems; constraint satisfaction problems; heuristic search; neuro-fuzzy approach; Computer science; Constraint optimization; Cost function; Engineering management; Fuzzy logic; Fuzzy sets; Fuzzy systems; Hopfield neural networks; Hybrid intelligent systems; Neural networks;
fLanguage
English
Journal_Title
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
Publisher
ieee
ISSN
1083-4419
Type
jour
DOI
10.1109/3477.809042
Filename
809042
Link To Document