A two-level distributed algorithm for nonconvex constrained optimization
From MaRDI portal
Publication:2696920
DOI10.1007/s10589-022-00433-4OpenAlexW4309878947MaRDI QIDQ2696920
Publication date: 17 April 2023
Published in: Computational Optimization and Applications (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1902.07654
Programming involving graphs or networks (90C35) Large-scale problems in mathematical programming (90C06) Nonconvex programming, global optimization (90C26) Nonlinear programming (90C30) Mathematical programming (90Cxx)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- A feasible method for optimization with orthogonality constraints
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Mathematical programming techniques in water network optimization
- Iteration complexity analysis of multi-block ADMM for a family of convex minimization without strong convexity
- Proximal alternating linearized minimization for nonconvex and nonsmooth problems
- On the linear convergence of the alternating direction method of multipliers
- A three-operator splitting scheme and its optimization applications
- An alternating direction algorithm for matrix completion with nonnegative factors
- On the sublinear convergence rate of multi-block ADMM
- On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators
- A dual algorithm for the solution of nonlinear variational problems via finite element approximation
- Global convergence of unmodified 3-block ADMM for a class of convex minimization problems
- A globally convergent algorithm for nonconvex optimization based on block coordinate update
- Structured nonconvex and nonsmooth optimization: algorithms and iteration complexity analysis
- A note on the alternating direction method of multipliers
- On the convergence analysis of the alternating direction method of multipliers with three blocks
- On non-ergodic convergence rate of Douglas-Rachford alternating direction method of multipliers
- Exact penalization and stationarity conditions of mathematical programs with equilibrium constraints
- On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming
- Multiplier and gradient methods
- The multiplier method of Hestenes and Powell applied to convex programming
- On the $O(1/n)$ Convergence Rate of the Douglas–Rachford Alternating Direction Method
- Alternating Direction Method with Gaussian Back Substitution for Separable Convex Programming
- Validation of nominations in gas network optimization: models, methods, and solutions
- A Convergent $3$-Block Semi-Proximal ADMM for Convex Minimization Problems with One Strongly Convex Block
- Convergence Analysis of Alternating Direction Method of Multipliers for a Family of Nonconvex Problems
- Strong SOCP Relaxations for the Optimal Power Flow Problem
- The Numerical Solution of Parabolic and Elliptic Differential Equations
- On the Numerical Solution of Heat Conduction Problems in Two and Three Space Variables
- Global Convergence of Splitting Methods for Nonconvex Composite Optimization
- On Augmented Lagrangian Methods with General Lower-Level Constraints
- Convergence properties of augmented Lagrangian methods for constrained global optimization
- On the Constant Positive Linear Dependence Condition and Its Application to SQP Methods
- On the Linear Convergence of the ADMM in Decentralized Consensus Optimization
- An alternating direction method of multipliers with a worst-case $O(1/n^2)$ convergence rate
- Random Gradient Extrapolation for Distributed and Stochastic Optimization
- Convergence of alternating direction method for minimizing sum of two nonconvex functions with linear constraints
- Alternating direction method of multipliers for real and complex polynomial optimization models
- Iteration-Complexity of Block-Decomposition Algorithms and the Alternating Direction Method of Multipliers
- A Distributed Approach for the Optimal Power-Flow Problem Based on ADMM and Sequential Convex Approximations
- On the Global Linear Convergence of the ADMM with MultiBlock Variables
- JuMP: A Modeling Language for Mathematical Optimization
- Augmented Lagrangian alternating direction method for matrix separation based on low-rank factorization
- The direct extension of ADMM for multi-block convex minimization problems is not necessarily convergent
