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Superlinear convergence of infeasible-interior-point methods for linear programming

Mathematical Programming, 1994
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhang, Yin, Zhang, Detong
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A truncated primal-infeasible dual-feasible network interior point method

Networks, 2000
Summary: The authors introduce the truncated primal-infeasible dual-feasible interior point algorithm for linear programming and describe an implementation of this algorithm for solving the minimum-cost network flow problem. In each iteration, the linear system that determines the search direction is computed inexactly, and the norm of the resulting ...
Portugal, L. F.   +3 more
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An interior point method for nonlinear programming with infeasibility detection capabilities

Optimization Methods and Software, 2014
This paper describes an interior point method for nonlinear programming endowed with infeasibility detection capabilities. The method is composed of two phases, a main phase whose goal is to seek optimality, and a feasibility phase that aims exclusively at improving feasibility.
Jorge Nocedal   +2 more
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Applying Infeasible Interior Point Method to SQP for Constrained Nonlinear Programming

2008 International Conference on Computer Science and Software Engineering, 2008
Active set (AS) method suffers deteriorating performance and premature convergence when it is faced with a nonlinear programming problem (NLP) consisting of several inequality constraints. Thus, we propose an SQP/IPM algorithm that uses infeasible interior point method (IIPM) for solving quadratic programming (QP) subproblems.
Hassan A. Bashir   +2 more
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A Infeasible Interior point homotopy method for solving linear complementarity problem

2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE), 2010
A global convergence Infeasible Interior point homotopy method for solving linear complementarity problem has been introduced in this paper. We give the homotopy equation and prove in details the existence of the smooth path from almost any positive orthant initial point to a solution of LCP. We give several preliminary numerical results.
null Junyan Xu   +2 more
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Infeasible interior point methods for sufficient linear complementarity problems

2009
In the first part of the thesis we focus on algorithms acting in the small neighborhood of the central path. We present a new first order corrector-predictor method for solving sufficient linear complementarity problems for which a sufficiently centered feasible starting point is available.
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Infeasible Interior Point Methods for Solving Linear Programs

1994
Interior point methods that follow the primal-dual central path of a dual pair of linear programs (P 0), (D 0) require that these problems are strictly feasible. To get around this difficulty, one technique is to embed (P 0), (D 0) into a family of suitably perturbed strictly feasible linear programs (P r), (D r), r ...
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Infeasible interior-point method for symmetric optimization using a positive-asymptotic barrier

Computational Optimization and Applications, 2018
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Petra Renáta Rigó, Zsolt Darvay
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A Infeasible Interior point homotopy method for solving horizontal linear complementarity problem

2011 International Conference on Computer Science and Service System (CSSS), 2011
A global convergence Infeasible Interior point homotopy method for solving horizontal linear complementarity problem has been introduced in this paper. We give the homotopy equation and prove in details the existence of the smooth path from almost any positive orthant initial point to a solution of HLCP.
null Junyan Xu   +2 more
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An improved and modified infeasible interior-point method for symmetric optimization

Asian-European Journal of Mathematics, 2016
In this paper an improved and modified version of full Nesterov–Todd step infeasible interior-point methods for symmetric optimization published in [A new infeasible interior-point method based on Darvay’s technique for symmetric optimization, Ann. Oper. Res. 211(1) (2013) 209–224; G. Gu, M. Zangiabadi and C.
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