Hopfield network and genetic algorithm to solve n-p hard optimization problem
Joint Authors
Source
International Journal of Intelligent Computing and Information Sciences
Issue
Vol. 6, Issue 2 (31 Jul. 2006)10 p.
Publisher
Ain Shams University Faculty of Computer and Information Sciences
Publication Date
2006-07-31
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
This paper presents a hybrid Hopfield neural network (HNN)-genetic algorithm (GA) approach to tackle the combinatorial optimization problem.
GAs is global search algorithms.
On the other hand, in HNN the range of a search is neighborhood of the initial point.
Then HNN is local search algorithm.
Our hybrid system utilizes the features of these algorithms that make up for defects of each other, so we can overcome some difficulties, such as coding and crossover in GAs and setting up the initial point and parameters in HNN model.
The effectiveness of our approach is demonstrated through reinvestigation of its capability of solving the traveling.
American Psychological Association (APA)
Margahny, M. H.& Salah, S.. 2006. Hopfield network and genetic algorithm to solve n-p hard optimization problem. International Journal of Intelligent Computing and Information Sciences،Vol. 6, no. 2.
https://search.emarefa.net/detail/BIM-284222
Modern Language Association (MLA)
Margahny, M. H.& Salah, S.. Hopfield network and genetic algorithm to solve n-p hard optimization problem. International Journal of Intelligent Computing and Information Sciences Vol. 6, no. 2 (Jul. 2006).
https://search.emarefa.net/detail/BIM-284222
American Medical Association (AMA)
Margahny, M. H.& Salah, S.. Hopfield network and genetic algorithm to solve n-p hard optimization problem. International Journal of Intelligent Computing and Information Sciences. 2006. Vol. 6, no. 2.
https://search.emarefa.net/detail/BIM-284222
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references.
Record ID
BIM-284222