Title :
An improved neural network approach to the traveling salesman problem
Author :
Gowda, Sudhir M. ; Lee, Bang W. ; Sheu, Sing J.
Author_Institution :
Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
Abstract :
To find the global minimum of an NP-complete problem within a reasonable computational time is extremely difficult. The traveling salesman problem, in addition to being NP-complete, has a complicated solution set in terms of optimizing an energy function. A novel neural network that removes ambiguities in the solution set and eliminates local minima is described. This network obtains the global minimum at a small increase in computational time when compared to the Hopfield network. Salient features of this improved network are presented
Keywords :
neural nets; operations research; optimisation; NP-complete problem; combinatorial optimisation; competitive networks modified Hopfield network; fixed starting city; global minimum; neural network; traveling salesman problem; Cities and towns; Computational complexity; Computer networks; Equations; Hopfield neural networks; NP-complete problem; Neural engineering; Neural networks; Polynomials; Traveling salesman problems;
Conference_Titel :
TENCON '89. Fourth IEEE Region 10 International Conference
Conference_Location :
Bombay
DOI :
10.1109/TENCON.1989.177000
