Results 21 to 30 of about 996 (126)
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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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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Computing Weighted Analytic Center for Linear Matrix Inequalities Using Infeasible Newton’s Method
Journal of Mathematics, 2015 We study the problem of computing weighted analytic center for system of linear matrix inequality constraints. The problem can be solved using Standard Newton’s method.
Shafiu Jibrin
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پژوهشهای ریاضی, 2021 By using a new search direction, we propose an infeasible interior-point method for monotone linear complementarity problem. The algorithm uses only one feasibility step in each iteration, and we prove that it suffices in order to obtain a polynomial ...
Nezameddin Mahdavi-Amiri +1 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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Optimal Control of Ascent Trajectory for Launch Vehicles: A Convex Approach
IEEE Access, 2019 This paper presents an online ascent trajectory optimization algorithm based on optimal control and convex optimization without accurate initial guesses.
Yuan Li +3 more
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A New Full-Newton Step $O(n)$ Infeasible Interior-Point Algorithm for $P_*(\kappa)$-horizontal Linear Complementarity Problems [PDF]
Computer Science Journal of Moldova, 2014 In this paper, we first present a brief review about the feasible interior-point algorithm for $P_*(\kappa)$-horizontal linear complementarity problems (HLCPs) based on new directions.
Soodabeh Asadi, Hossein Mansouri
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IEEE Access, 2019 In this work, by considering a variety of realistic hardware impairments, we aim to enhance the security of a cooperative relaying network, where a source intends to transmit its confidential information to a destination in the presence of a group of ...
Majid Moradikia +4 more
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Journal of Numerical Analysis and Approximation TheoryThe focus of this research is to apply primal-dual interior-point pathfollowing methods, specifically those derived from Newton’s method for solving convex quadratic semidefinite optimization (CQSDO) problems. In this paper, we present a numerical study
Yasmina Bendaas, Mohamed Achache
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A preconditioned inexact infeasible quantum interior point method for linear optimization
Computational Optimization and ApplicationsAbstract Quantum Interior Point Methods (QIPMs) have been attracting significant interests recently due to their potential of solving optimization problems substantially faster than state-of-the-art conventional algorithms. In general, QIPMs use Quantum Linear System Algorithms (QLSAs) to substitute classical linear system solvers ...
Zeguan Wu, Xiu Yang, Tamás Terlaky
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