Two Classes Of Methods For Nonlinear Programming

In this paper, two classes of methods for nonlinear programming:filter method and filled function method are concerned.Firstly, a conjugate projection filter algorithm for inequality constrained optimization is presented. It has three advantages. The first one is that the amount of computation is lower because the gradient matrix only needs to be computed one time at each iterate. The second one is that the penalty function is not required by the filter method. The third one is that under some mild conditions the global convergence and local super-linearly convergence can be induced.Secondly, a class of discrete filled function for discrete global optimization problem is proposed. The discrete properties of the filled function are proved and a new filled function algorithm is designed. A few numerical tests have proved that our algorithm is effective in solving discrete global optimization problems.