Title :
A neural network shortest path algorithm
Author :
Haines, Trenton ; Medanic, Juraj V.
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL, USA
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;
Conference_Titel :
Intelligent Control, 1994., Proceedings of the 1994 IEEE International Symposium on
Conference_Location :
Columbus, OH
Print_ISBN :
0-7803-1990-7
DOI :
10.1109/ISIC.1994.367787
