Letters: An improved elastic net method for traveling salesman problem

Authors:
Junyan Yi;Gang Yang;Zhiqiang Zhang;Zheng Tang
Affiliations:
Faculty of Engineering, University of Toyama, Toyama-shi 930-8555, Japan;Faculty of Engineering, University of Toyama, Toyama-shi 930-8555, Japan;Faculty of Engineering, University of Toyama, Toyama-shi 930-8555, Japan;Faculty of Engineering, University of Toyama, Toyama-shi 930-8555, Japan
Venue:
Neurocomputing
Year:
2009

Citing 2
Cited 1

On the stability of the travelling salesman problem algorithm of Hopfield and Tank

Biological Cybernetics
An analysis of the elastic net approach to the traveling salesman problem

Neural Computation

Solving the traveling salesman problem based on an adaptive simulated annealing algorithm with greedy search

Applied Soft Computing

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Abstract

In this article, we propose a new elastic net method to solve the traveling salesman problem by introducing some time-dependent parameters. This method can help network neurons move quickly near to the cities at early stage, and gradually increase the strength that pulls neurons towards their neighbours on the path to minimize the total path length. This enables the network to have superior ability of searching for cities, and converge sooner to a saturated state. Simulation results illustrate that the proposed network performs better than the classical elastic net for optimization both in solution quality and convergence speed.