An inexact infeasible arc-search interior-point method for linear optimization problems

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Iida, Einosuke, Yamashita, Makoto
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Optimization and Control Numerical Analysis 90C51, 65K05, 90C05 F.2.1; G.1.6
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

An infeasible interior-point arc-search method with Nesterov's restarting strategy for linear programming problems
di: Iida, Einosuke, et al.
Pubblicazione: (2023)

A preconditioned inexact infeasible quantum interior point method for linear optimization
di: Wu, Zeguan, et al.
Pubblicazione: (2024)

On the asymptotic behavior of a higher-order extrapolation primal-dual interior-point method for nonlinear programming
di: Heeman, Pim, et al.
Pubblicazione: (2025)

A novel numerical method tailored for unconstrained optimization problems
di: Li, Lin, et al.
Pubblicazione: (2025)

A polynomial time infeasible interior-point arc-search algorithm for convex optimization
di: Yang, Yaguang
Pubblicazione: (2022)

Extragradient method with feasible inexact projection to variational inequality problem
di: Millán, R. Díaz, et al.
Pubblicazione: (2023)

Active set identification and rapid convergence for degenerate primal-dual problems
di: Díaz, Mateo, et al.
Pubblicazione: (2026)

An interior point method for nonlinear constrained derivative-free optimization
di: Brilli, Andrea, et al.
Pubblicazione: (2021)

Joint Pricing and Matching for Resource Allocation Platforms via Min-cost Flow Problem
di: Hikima, Yuya, et al.
Pubblicazione: (2024)

Stochastic momentum ADMM for nonconvex and nonsmooth optimization with application to PnP algorithm
di: Deng, Kangkang, et al.
Pubblicazione: (2025)

A Primal-Dual Frank-Wolfe Algorithm for Linear Programming
di: Hough, Matthew, et al.
Pubblicazione: (2024)

A Massively Parallel Interior-Point Method for Arrowhead Linear Programs with Local Linking Structure
di: Kempke, Nils-Christian, et al.
Pubblicazione: (2024)

Optimization in Theory and Practice
di: Wright, Stephen J.
Pubblicazione: (2025)

The Global R-linear Convergence of Nesterov's Accelerated Gradient Method with Unknown Strongly Convex Parameter
di: Bao, Chenglong, et al.
Pubblicazione: (2023)

Design Guidelines for Noise-Tolerant Optimization with Applications in Robust Design
di: Lou, Yuchen, et al.
Pubblicazione: (2024)

An Interior-Point Algorithm for Continuous Nonlinearly Constrained Optimization with Noisy Function and Derivative Evaluations
di: Curtis, Frank E., et al.
Pubblicazione: (2025)

Zeroth-order gradient estimators for stochastic problems with decision-dependent distributions
di: Hikima, Yuya, et al.
Pubblicazione: (2025)

Complexity of an inexact stochastic SQP algorithm for equality constrained optimization
di: O'Neill, Michael J., et al.
Pubblicazione: (2026)

A Riemannian Variational and Spectral Framework for High-Dimensional Sphere Packing: Barrier-Dynamics Reconciliation, Periodic Rigidity, and Discrete-Time Guarantees
di: Alpay, Faruk, et al.
Pubblicazione: (2025)

Implementing a unified solver for nonlinearly constrained optimization
di: Vanaret, Charlie, et al.
Pubblicazione: (2024)

Where's Ben Nevis? A 2D optimisation benchmark with 957,174 local optima based on Great Britain terrain data
di: Wei, Yuhang, et al.
Pubblicazione: (2024)

Data-Dependent Complexity of First-Order Methods for Binary Classification
di: Hough, Matthew, et al.
Pubblicazione: (2025)

Projections onto Spectral Matrix Cones
di: Cederberg, Daniel, et al.
Pubblicazione: (2025)

Gradient Descent Methods for Regularized Optimization
di: Nikolovski, Filip, et al.
Pubblicazione: (2024)

Anderson Accelerated Primal-Dual Hybrid Gradient for solving LP
di: Zhou, Yingxin, et al.
Pubblicazione: (2025)

On the local and global minimizers of the smooth stress function in Euclidean Distance Matrix problems
di: Song, Mengmeng, et al.
Pubblicazione: (2024)

Escaping Saddle Points via Curvature-Calibrated Perturbations: A Complete Analysis with Explicit Constants and Empirical Validation
di: Alpay, Faruk, et al.
Pubblicazione: (2025)

Adaptive Stochastic Gradient Descent Ascent Algorithm for Nonconvex Minimax Problems with Decision-Dependent Distributions
di: Gao, Yan, et al.
Pubblicazione: (2025)

Accelerated Gradient Methods with Gradient Restart: Global Linear Convergence
di: Bao, Chenglong, et al.
Pubblicazione: (2024)

First-order penalty methods for bilevel optimization
di: Lu, Zhaosong, et al.
Pubblicazione: (2023)

Tight Error Bounds for the Sign-Constrained Stiefel Manifold
di: Chen, Xiaojun, et al.
Pubblicazione: (2022)

Unbelievable $O(L^{1.5})$ worst case computational complexity achieved by $spdspds$ algorithm for linear programming problem
di: Halemane, Keshava Prasad
Pubblicazione: (2014)

Monomial barrier functions for the box-constrained convex optimization problems
di: Fayed, Hatem
Pubblicazione: (2024)

Sufficiently Regularized Nonnegative Quartic Polynomials are Sum-of-Squares
di: Zhu, Wenqi, et al.
Pubblicazione: (2026)

Oracle complexities of augmented Lagrangian methods for nonsmooth manifold optimization
di: Deng, Kangkang, et al.
Pubblicazione: (2024)

Variance-reduced first-order methods for deterministically constrained stochastic nonconvex optimization with strong convergence guarantees
di: Lu, Zhaosong, et al.
Pubblicazione: (2024)

A first-order augmented Lagrangian method for constrained minimax optimization
di: Lu, Zhaosong, et al.
Pubblicazione: (2023)

ASMOP: Additional sampling stochastic trust region method for multi-objective problems
di: Jerinkić, Nataša Krklec, et al.
Pubblicazione: (2025)

Bregman proximal gradient method for linear optimization under entropic constraints
di: Briceño-Arias, Luis M., et al.
Pubblicazione: (2025)

A first-order method for nonconvex-strongly-concave constrained minimax optimization
di: Lu, Zhaosong, et al.
Pubblicazione: (2025)