A neural network shortest path algorithm

Author

Haines, Trenton ; Medanic, Juraj V.

Author_Institution

Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL, USA

fYear

1994

fDate

16-18 Aug 1994

Firstpage

382

Lastpage

387

Abstract

This paper develops a neural network implementation of a shortest path algorithm using a Hopfield network architecture. The main advantage of this neural network is that the number of neurons in the network grows linearly with the number of links in the graph instead of growing with the square of the number of nodes in the graph, as is the case with existing algorithms. The properties of this neural network are then investigated and its performance is evaluated through an extensive simulation study

Keywords

Hopfield neural nets; graph theory; optimisation; performance evaluation; Hopfield network architecture; graph theory; neural network; performance evaluation; shortest path algorithm; Computational modeling; Costs; Equations; Hopfield neural networks; Iterative algorithms; Neural network hardware; Neural networks; Neurons; Polynomials; Transportation;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control, 1994., Proceedings of the 1994 IEEE International Symposium on

Conference_Location

Columbus, OH

ISSN

2158-9860

Print_ISBN

0-7803-1990-7

Type

conf

DOI

10.1109/ISIC.1994.367787

Filename

367787

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2380370