This paper presents a new approach to solve line-balancing problems using the discrete and linked state transition neural networks whose feasibility for the constraints is kept by cooperative and simultaneous change of the neurons states. The simulation results for the simple line-balancing problems demonstrate more effective global convergence than Hopfield's neural networks
