1 research outputs found
An Improved Sequential Quadratic Programming Algorithm for Solving General Nonlinear Programming Problems
In this paper, a class of general nonlinear programming problems with
inequality and equality constraints is discussed. Firstly, the original problem
is transformed into an associated simpler equivalent problem with only
inequality constraints. Then, inspired by the ideals of sequential quadratic
programming (SQP) method and the method of system of linear equations (SLE), a
new type of SQP algorithm for solving the original problem is proposed. At each
iteration, the search direction is generated by the combination of two
directions, which are obtained by solving an always feasible quadratic
programming (QP) subproblem and a SLE, respectively. Moreover, in order to
overcome the Maratos effect, the higher-order correction direction is obtained
by solving another SLE. The two SLEs have the same coefficient matrices, and we
only need to solve the one of them after a finite number of iterations. By a
new line search technique, the proposed algorithm possesses global and
superlinear convergence under some suitable assumptions without the strict
complementarity. Finally, some comparative numerical results are reported to
show that the proposed algorithm is effective and promising