SOLVING COMBINATORIAL OPTIMIZATION PROBLEMS USING THE OSCILLATORY NEURAL-NETWORK

The Hopfield neural network for optimization problems often falls into local minima. To escape from the local minima. the neuron unit in the neural network is modified to become an oscillatory unit by adding a simple self-feedback circuit. By combining the oscillatory unit with a n energy-value extraction circuit, an oscillatory neural network is co nstructed. The network can repeatedly extract solutions, and can simul taneously evaluate them. In this paper, the network is applied to four NP-complete problems to demonstrate its generality and efficiency. Th e network can serve each problem and can obtain better solutions than the original Hopfield neural network and simple algorithms.