Results 11 to 20 of about 1,060 (116)
An Inexact Feasible Quantum Interior Point Method for Linearly Constrained Quadratic Optimization
Entropy, 2023 Quantum linear system algorithms (QLSAs) have the potential to speed up algorithms that rely on solving linear systems. Interior point methods (IPMs) yield a fundamental family of polynomial-time algorithms for solving optimization problems. IPMs solve a
Zeguan Wu +4 more
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Sensors, 2022 The creation of accurate three-dimensional models has been radically simplified in recent years by developing photogrammetric methods. However, the photogrammetric procedure requires complex data processing and does not provide an immediate 3D model, so ...
Piotr Łabędź +5 more
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A Full-Newton step infeasible-interior-point algorithm for P*(k)-horizontal linear complementarity problems [PDF]
Yugoslav Journal of Operations Research, 2015 In this paper we generalize an infeasible interior-point method for linear optimization to horizontal linear complementarity problem (HLCP). This algorithm starts from strictly feasible iterates on the central path of a perturbed problem that is
Asadi S., Mansouri H.
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ISPRS Open Journal of Photogrammetry and Remote Sensing, 2022 Historical terrestrial images are the only visual sources documenting alpine environments shortly after the end of the Little Ice Age. Despite their unique value, they are largely unused for quantifying environmental changes because of the difficult and ...
Sebastian Mikolka-Flöry +3 more
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Convergence Analysis of an Inexact Infeasible Interior Point Method for Semidefinite Programming [PDF]
Computational Optimization and Applications, 2004 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Stefania Bellavia, Sandra Pieraccini
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Counterexample to a Conjecture on an Infeasible Interior-Point Method
SIAM Journal on Optimization, 2010 Summary: In [the second author, SIAM J. Optim. 16, No.~4, 1110--1136 (2006; Zbl 1131.90029)], Roos proved that the devised full-step infeasible algorithm has \(O(n)\) worst-case iteration complexity. This complexity bound depends linearly on a parameter \(\bar{\kappa}(\zeta)\), which is proved to be less than \(\sqrt{2n}\).
Gu, G. (author), Roos, C. (author)
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On the behavior of Lagrange multipliers in convex and nonconvex infeasible interior point methods [PDF]
Mathematical Programming, 2019 We analyze sequences generated by interior point methods (IPMs) in convex and nonconvex settings. We prove that moving the primal feasibility at the same rate as the barrier parameter $μ$ ensures the Lagrange multiplier sequence remains bounded, provided the limit point of the primal sequence has a Lagrange multiplier.
Gabriel Haeser +2 more
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Communications in Combinatorics and Optimization, 2018 An infeasible interior-point algorithm for solving the $P_*$-matrix linear complementarity problem based on a kernel function with trigonometric barrier term is analyzed.
B. Kheirfam, M. Haghighi
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Convergence Analysis of the Inexact Infeasible Interior-Point Method for Linear Optimization [PDF]
Journal of Optimization Theory and Applications, 2008 This article studies the use of a primal-dual interior point method for solving large scale linear programs. The article begins with a presentation of the background to this problem and an overview of the existing literature, including the use of Preconditioned Conjugate Gradients (PCG) for inexact infeasible path-following algorithms.
Al-Jeiroudi, G., Gondzio, J.
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A penalty barrier framework for nonconvex constrained optimization [PDF]
Journal of Nonsmooth Analysis and OptimizationWe consider minimization problems with structured objective function and smooth constraints, and present a flexible framework that combines the beneficial regularization effects of (exact) penalty and interior-point methods.
Alberto De Marchi, Andreas Themelis
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