A Fast and Reliable Approach to TSP using Positively Self-feedbacked Hopfield Networks

摘要

Abstract in this paper, a fast and reliable approach to the Traveling Salesman Problem (TSP) using the positively self-feedbacked Hopfield networks is proposed. The Hopfield networks with positive self-feedbacks and its collective computational properties are studied. It is proved theoretically and confirmed by simulating the randomly generated Hopfield network with positive self-feedbacks that the emergent collective properties of the original Hopfield network also are present in this network. The network is applied to the TSP and results of computer simulations are presented and used to illustrate the computation power of the networks. The simulation results show that the Hopfield networks with positive self-feedbacks has a rate of success higher than the original Hopfield network for solving the TSP, and converges faster to stable solution than the original Hopfield network does.