A SUPERLINEAR CONVERGENCE MODIFIED FSQP METHOD FOR LINEAR CONSTRAINED OPTIMIZATION PROBLEMS

In this paper, a modified feasible sequential quadratic programming (FSQP) method is presented to solve the linear programming. By solving only one QP subproblem, a feasible descent direction is obtained. A high-order revised direction is computed by solving a linear system to avoid Maratos effect. Under some suitable conditions, the global and superlinear convergence can be obtained. Keywords: FSQP method; Llinear constrained optimization; Global convergence; superlinear convergence rate