A Neural Network Based on Algorithm for Traveling Salesman Problem
Abstract
This paper construct a neural network based algorithm to solve the traveling salesman problem. The performance of the algorithm is evaluated through simulating 100 randomly generated instances of the 10-city traveling salesman problems. The performance of the proposed learning method on these test problems is very satisfactory in terms of solution quality.
Keywords
Full Text:
PDFReferences
P.W. Protzel, D. L. Plumbo, and M. K. Arras, “Performance and fault-tolerance of neural network for optimization,” IEEE Trans. Neural Networks, vol.4, pp.600-614, 1993.
Y. Takefuji and K. C. Lee, “Artificial neural networks for four-coloring map problems and K-colorability problems,” IEEE Trans. Circuits Syst., vol.38, no. 3, pp.326-333, Mar. 1991.
Y. Takefuji and K. C. Lee, “An artificial hysteresis binary neuron: A model suppressing the oscillatory behaviors of neural dynamics,” Biol. Cybern., vol.64, pp.353-356, 1991.
DOI: https://doi.org/10.18686/mcs.v4i4.1600
Refbacks
- There are currently no refbacks.
