A Modified Sequence Quadratic Programming Method for Nonlinear Programming

Abstract

Sequence quadratic programming method is one of the most useful methods for solving constrained optimization problem. In this paper, a new modified SQP method is proposed to solve the nonlinear programming. This algorithm starts from an arbitrary initial point and adjusts penalty parameter automatically. A descent direction is obtained by solving only one variant constrained sub problem. In order to avoid Marotos effect, a high-order revised direction is obtained by solving a line system. Furthermore, under mild conditions, the global and local super linear convergence properties are obtained.