Scheduling Mutiprocessor Job Using Hopfield Neural Network
Xiu Wang · Systems engineering and electronics · 2002
Multiprocessor job scheduling is a complicated combinatorial optimization problem, and the Hopfield neural network is extensively applied to solve various combinatorial optimization problems. An effective Hopfield neural network (HNN) approach to multiprocessor job scheduling problem (known to be a NP hard problem)is proposed, which is apt to resource and timing (execution time and deadline) constraints. This approach directly formulates the energy function of HNN according to constraints term by term and derives HNN model. Simulation results demonstrate that the derived energy function works effectively for this class of problems.