Optimization method of 0-1 integral programming using Hopfield neural networks analysis

A new approach is presented to optimize the 0 - 1 integral linear and quadratic programming (0 - 1 ILQP) using Hopfield neural networks. First, the objective function and the constraints are integrated an integer in the form of energy function with penalty function approach. Then, the global minimal point of the energy function, which also is the optimal solution of the 0 - 1 ILQP, is obtained by using Hopfield neural networks. Finally, an application to optimizing the mission schedule of satellite is presented as an example that is solved successfully with the approach.