A constrained optimization neural net technique for economic power dispatch

A linear programming neural network is extended to quadratic programming problems with both linear equality and inequality constraints. It is shown that the equilibrium of the quadratic programming network is asymptotically stable and is in the neighborhood of the minimizer of the objective function. The equilibrium can be made arbitrarily close to the minimizer of the objective function by choosing a parameter sufficiently large. An economic power dispatch problem is simulated to demonstrate the dynamic behavior of the proposed quadratic programming network