Results 201 to 210 of about 16,553,811 (242)
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SIAM Journal on Optimization, 1994
Interior-point methods require strictly feasible points as starting points. In theory, this requirement does not seem to be particularly restrictive, but it can be costly in computation. To overcome this deficiency, most existing practical algorithms allow positive but infeasible starting points and seek feasibility and optimality simultaneously ...
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Interior-point methods require strictly feasible points as starting points. In theory, this requirement does not seem to be particularly restrictive, but it can be costly in computation. To overcome this deficiency, most existing practical algorithms allow positive but infeasible starting points and seek feasibility and optimality simultaneously ...
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Convergence of the homotopy path for a full-Newton step infeasible interior-point method
Operations Research Letters, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Alireza Asadi, Guoyong Gu, Cornelis Roos
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On the convergence of an infeasible primal-dual interior-point method for convex programming
Optimization Methods and Software, 1994We consider the infeasible primal-dual algorithm for smooth convex programming recently introduced by Vial [15]. We show, under mild assumptions, that a “SUMT” or “long-step path following” version of the algorithm is globally convergent. The stepiength on each iteration is based on a merit function which is a modification of the potential function ...
Kurt M. Anstreicher, Jean-Philippe Vial
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An improved and modified infeasible interior-point method for symmetric optimization
Asian-European Journal of Mathematics, 2016In 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.
Behrouz Kheirfam
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An Infeasible Interior-Point Method with Nonmonotonic Complementarity Gaps
Optimization Methods and Software, 2002This article describes an infeasible interior-point (IP) method for solving monotone variational inequality problems with polyhedral constraints and, as a particular case, monotone nonlinear complementarity problems. The method determines a search direction by solving, possibly in an inexact way, the Newton equation for the central path.
GASPARO M. G +2 more
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An Infeasible-Interior-Point Method for Linear Complementarity Problems
SIAM Journal on Optimization, 1997In this work we present an infeasible-interior-point algorithm which is based on a method for the general nonlinear programming problem to solve linear complementarity problems. For this algorithm, we prove global convergence from any strictly positive starting point, under minor assumptions.
Evangelia M. Simantiraki +1 more
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An interior point method for nonlinear programming with infeasibility detection capabilities
Optimization Methods and Software, 2014This 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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New infeasible interior-point algorithm based on monomial method
Computers & Operations Research, 1996zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yi-Chih Hsieh, Dennis L. Bricker
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Validated Infeasible Interior-Point Predictor–Corrector Methods for Linear Programming
Numerical Algorithms, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ismail I. Idriss, Wolfgang V. Walter
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A truncated primal-infeasible dual-feasible network interior point method
Networks, 2000Summary: 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 ...
Luis F. Portugal +3 more
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