Revisions of constraint approximations in the successive QP method for nonlinear programming problems

In the last few years the successive quadratic programming methods proposed by Han and Powell have been widely recognized as excellent means for solving nonlinea programming problems.However, there remain some questions about their linear approximations to the constraints from both theoretical and empirical points of view.In this paper, we propose two revisions of the linear approximation to the constraints and show that the directions generated by the revisions are also descent directions of exact penalty functions of nonlinear programming problems. The new technique can cope better with bad starting points than the usual one.