A Strategy for Global Convergence in a Sequential Quadratic Programming Algorithm

n a previous work [P. Boggs and J. Tolle, SIAM J. Numer. Anal., 21 (1984), pp. 1146–1161], the authors introduced a merit function for use with the sequential quadratic programming (SQP) algorithm for solving nonlinear programming problems. Here, further theoretical justification, including a global convergence theorem, is provided. In addition, modifications are suggested that allow the efficient implementation of the merit function while maintaining the important convergence properties. Numerical results are presented demonstrating the effectiveness of the procedure.