Title :
A recurrent neural network for solving the shortest path problem
Author_Institution :
Dept. of Ind. Technol., North Dakota Univ., Grand Forks, ND, USA
fDate :
30 May-2 Jun 1994
Abstract :
The shortest path problem is the classical combinatorial optimization problem arising in numerous planning and designing contexts. In this paper, a recurrent neural network for solving the shortest path problem is presented. The proposed recurrent neural network is able to generate optimal solutions to the shortest path problem. The performance and operating characteristics of the recurrent neural network are demonstrated by use of illustrative examples
Keywords :
combinatorial mathematics; optimisation; recurrent neural nets; combinatorial optimization problem; operating characteristics; optimal solutions; recurrent neural network; shortest path problem; Costs; Design optimization; Neodymium; Neural networks; Path planning; Recurrent neural networks; Robots; Routing; Shortest path problem; Transportation;
Conference_Titel :
Circuits and Systems, 1994. ISCAS '94., 1994 IEEE International Symposium on
Conference_Location :
London
Print_ISBN :
0-7803-1915-X
DOI :
10.1109/ISCAS.1994.409590
