Feb 1, 1994 · In practice, these methods have demonstrated superior computational performance. From a theoretical point of view, however, they have not been ...
At present the interior-point methods of choice are primal—dual infeasible-interior-point methods, where the iterates are kept positive, but allowed to be ...
Optimization, 3 (1993), pp. 118-133. [23] , Superlinear and quadratic convergence of primal-dual interior point algorithms for linear programming ...
Jan 12, 2024 · In this paper, we propose a practical initial iterate to an implementable infeasible interior point algorithm that guarantees superlinear ...
In this paper, we focus on an infeasible predictor–corrector primal–dual path following interior point algorithm to solve the homogeneous feasibility model [ ...
Weillustrate the usefulness of these bounds by establishing thesuperlinear convergence of the algorithm presented in Wright andRalph [22] for solving the ...
Aug 27, 2023 · In this paper, we propose a practical initial iterate to an implementable infeasible interior point algorithm that guarantees superlinear ...
May 1, 1996 · In this paper, we propose an algorithm for solving monotone geometrical LCPs, and we prove its superlinear convergence without the strictly ...
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Weillustrate the usefulness of these bounds by establishing thesuperlinear convergence of the algorithm presented in Wright andRalph [22] for solving the ...
On the other hand, superlinearly convergent interior-point methods often achieve good accuracy (duality measure of 10−10 or better) in substantially fewer ...