This paper establishes the superlinear convergence of a symmetric primal-dual path following algorithm for semidefinite programming under the assumptions that the semidefinite program has a strictly complementary primal-dual optimal solution and that the size of the central path neighborhood...

In this paper, we propose a new sequential systems of linear equations (SSLE) filter algorithm, which is an infeasible QP-free method. The new algorithm needs to solve a few reduced systems of linear equations with the same nonsingular coefficient matrix, and after finitely many iterations, only...

In many decision problems, criteria occur that can be expressed as ratios. The corresponding optimization problems are nonconvex programs of fractional type. In this paper, an algorithm for the numerical solution of these problems is introduced that converges always at superlinear speed....

In this paper, we present a new trust region method for unconstrained nonlinear programming in which we blend adaptive trust region algorithm by non-monotone strategy to propose a new non-monotone trust region algorithm with automatically adjusted radius. Both non-monotone strategy and adaptive...

A new predictor--corrector interior point algorithm for solving monotone linear complementarity problems (LCP) is proposed, and it is shown to be superlinearly convergent with at least order 1.5, even if the LCP has no strictly complementary solution. Unlike Mizuno's recent algorithm (Mizuno,...

In this paper, a Newton-like method for variational inequality problems is considered. One feature of the algorithm is that only the solution of linear systems of equations is required at each iteration and that the strict complementarity assumption is never invoked. Another is that under mild...

In this paper, a Newton-like method for variational inequality problems is considered. One feature of the algorithm is that only the solution of linear systems of equations is required at each iteration and that the strict complementarity assumption is never invoked. Another is that under mild...

This paper establishes the superlinear convergence of a symmetric primal-dual path following algorithm for semidefinite programming under the assumptions that the semidefinite program has a strictly complementary primal-dual optimal solution and that the size of the central path neighborhood...

A new predictor--corrector interior point algorithm for solving monotone linear complementarity problems (LCP) is proposed, and it is shown to be superlinearly convergent with at least order 1.5, even if the LCP has no strictly complementary solution. Unlike Mizuno's recent algorithm (Mizuno,...