A real-time solution for the traveling salesman problem using a Boolean neural network

It is shown that the Boolean neural network can be used to solve NP-complete problems. The problem under consideration is the traveling salesman problem. The Boolean neural network is modified to include the iterative procedure for solving combinatorial optimization problems. An architecture that utilizes this modified Boolean neural network is proposed for solving this problem. The simulation results are found to be comparable to the simulated annealing algorithm, which is used as a test base. The results show a better variance as compared to simulated annealing. The modified Boolean neural network implementation involves lesser hardware complexity, good noise immunity and faster circuitry