Performance of quadratic assignment problem by hopfield NN with periodic brake

Solving combinatorial optimization problems is one of the important applications of neural networks. Many researchers have proposed noise induced hopfield neural networks in which noises are induced state values of neurons. However, the noise inducing method to state values of neurons cause problems. In this study, we propose hopfield neural networks with periodic brake. In the proposed system, external noises are not induced to state values of neurons. Thus, the proposed system can avoid the problem caused in the noise induced system. We investigate the solving ability of the proposed system for quadratic assignment problems and designing of parameters.