A new method for nonlinearly constrained optimization

Abstract
A new penalty function method of solving problems involving a nonlinear objective function subject to nonlinear equality and inequality constraints is described. It ameliorates difficulties experienced with the illconditioning of the Hessian matrix of classical penalty function methods. Experience based on the solution of 25 test problems indicates the proposed method is as good as, or better, than methods that are now being used.