A BOOLEAN NEURAL-NETWORK APPROACH FOR THE TRAVELING SALESMAN PROBLEM

It is shown that the Boolean neural network can be used to solve NP-co mplete problems. The problem under consideration is the traveling sale sman problem. The Boolean neural network has been modified to include the iterative procedure for solving combinatorial optimization problem s. An architecture that utilizes this modified Boolean neural network (MBNN) is proposed for solving this problem. The simulation results ha ve been found to be comparable to the simulated annealing algorithm (S AA), which is used as a test base. The MBNN implementation involves lo w hardware complexity, good noise immunity, and fast circuitry. This i s very important in real-time systems and commercial job scheduling ap plications.