Improving the Performance of the Hopfield Network By Using A Relaxation Rate

摘要

In the Hopfield network, a solution of an optimiization problem is obtained after the network is relaxed to an equilibrium state. This paper shows that the performance of the Hopfield network can be improved by using a relaxation rate to control the relaxation process. Analysis suggests that the relaxation process has an important impact on the quality of a solution. A relaxation rate is then introduced to control the relaxation process in order to achieve solutions with better quality. Two types of relaxation rate (constant and dynamic) are proposed and evaluated through simulations based on 200 randomly generated city distributions of the 10-city traveling salesman problem. The result shows that using a relaxation rate can decrease the error rate by 9.87precent as compared to those without using a relaxation rate. Using a dynamic relaxation rate can further decrease the error rate by 4.2precent and increase the percentage of valid tours by 0.4precent as compared to those using a constant relaxation rate.