A Fast Elastic Net Method for Traveling Salesman Problem

In this paper, we proposed a fast method for improving the elastic net to solve the traveling salesman problem. A dynamic parameter strategy is introduced into the elastic net, which increases the ability of searching for the cities and helps the network get convergence with the optimal or near-optimal solution sooner. Simulations show that the proposed method is superior to the classical elastic net and some other neural networks both in light of solution quality and convergence speed.