[HTML][HTML] Hierarchical distributed optimization of constraint-coupled convex and mixed-integer programs using approximations of the dual function
In this paper, two new algorithms for dual decomposition-based distributed optimization are
presented. Both algorithms rely on the quadratic approximation of the dual function of the …
presented. Both algorithms rely on the quadratic approximation of the dual function of the …
A hierarchical dual decomposition-based distributed optimization algorithm combining quasi-Newton steps and bundle methods
V Yfantis, M Ruskowski - 2022 30th Mediterranean Conference …, 2022 - ieeexplore.ieee.org
This paper presents a hierarchical distributed optimization algorithm based on quasi-
Newton update steps. Separable convex optimization problems are decoupled through dual …
Newton update steps. Separable convex optimization problems are decoupled through dual …
Primal recovery from consensus-based dual decomposition for distributed convex optimization
A Simonetto, H Jamali-Rad - Journal of Optimization Theory and …, 2016 - Springer
Dual decomposition has been successfully employed in a variety of distributed convex
optimization problems solved by a network of computing and communicating nodes. Often …
optimization problems solved by a network of computing and communicating nodes. Often …
Derivative-free method for composite optimization with applications to decentralized distributed optimization
In this paper, we propose a new method based on the Sliding Algorithm from Lan (2016,
2019) for the convex composite optimization problem that includes two terms: smooth one …
2019) for the convex composite optimization problem that includes two terms: smooth one …
A Numerical Study on the Parallelization of Dual Decomposition-based Distributed Mixed-Integer Programming
The shift from centralized to decentralized systems is increasing the complexity of many
problems in control and optimization. However, it also presents the opportunity to exploit …
problems in control and optimization. However, it also presents the opportunity to exploit …
Proximal nested primal-dual gradient algorithms for distributed constraint-coupled composite optimization
J Li, Q An, H Su - Applied Mathematics and Computation, 2023 - Elsevier
In this paper, we study a class of distributed constraint-coupled optimization problems,
where each local function is composed of a smooth and strongly convex function and a …
where each local function is composed of a smooth and strongly convex function and a …
Distributed optimization for convex mixed-integer programs based on projected subgradient algorithm
Convex Mixed-Integer Program (MIP) has received extensive attention due to its wide
applications. This paper proposes a distributed optimization algorithm based on Projected …
applications. This paper proposes a distributed optimization algorithm based on Projected …
A two-level distributed algorithm for nonconvex constrained optimization
This paper aims to develop distributed algorithms for nonconvex optimization problems with
complicated constraints associated with a network. The network can be a physical one, such …
complicated constraints associated with a network. The network can be a physical one, such …
Nested Primal-dual Gradient Algorithms for Distributed Constraint-coupled Optimization
J Li, H Su - arXiv preprint arXiv:2205.11119, 2022 - arxiv.org
We study a class of distributed optimization problems with a globally coupled equality
constraint. A novel nested primal-dual gradient algorithm (NPGA) is proposed from the dual …
constraint. A novel nested primal-dual gradient algorithm (NPGA) is proposed from the dual …
Distributed Primal–Dual Splitting Algorithm for Multiblock Separable Optimization Problems
This article considers the distributed structured optimization problem of collaboratively
minimizing the global objective function composed of the sum of local cost functions. Each …
minimizing the global objective function composed of the sum of local cost functions. Each …