A new SQP method of feasible directions for nonlinear programming

In this paper, a new sequential quadratic programming (SQP) method of feasible directions is proposed and analyzed for nonlinear programming, where a feasible direction of descent can be derived from solving only one QP subproblem. In particular, this method can produce automatically a revised direction with the explicit expression which can avoid Maratos effect without solving QP subproblem. The theoretical analysis shows that global and superlinear convergence can be induced. In the end, numerical experiment is given to illustrate the effectiveness of the method.

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