Proceedings ArticleDOI
Distributed convex stochastic optimization under few constraints in large networks
Romain Couillet,Pascal Bianchi,Jérémie Jakubowicz +2 more
- pp 289-292
Reads0
Chats0
TLDR
This article introduces a distributed convex optimization algorithm in a constrained multi-agent system composed by a large number of nodes that alleviates several limitations of algorithms proposed in the stochastic optimization literature.Abstract:
This article introduces a distributed convex optimization algorithm in a constrained multi-agent system composed by a large number of nodes. We focus on the case where each agent seeks to optimize its own local parameter under few coupling equality and inequality constraints. The objective function is of the power flow type and can be decoupled as a sum of elementary functions, each of which assumed (imperfectly) known by only one node. Under these assumptions, a cost-efficient decentralized iterative solution based on Lagrangian duality is derived, which is provably converging. This new approach alleviates several limitations of algorithms proposed in the stochastic optimization literature. Applications are proposed to decentralized power flow optimization in smart grids.read more
Citations
More filters
Journal ArticleDOI
Methodology for multiarea state estimation solved by a decomposition method
TL;DR: In this article, a decentralized optimization scheme with minimum information exchange among subsystems is proposed to solve the multi-area state estimation problem by a decomposition method, which is derived from the Lagrangian relaxation method and is named optimality condition decomposition.
Book ChapterDOI
Optimization classification and techniques of WSNs in smart grid
Muhammad Naeem,Muhammad Naeem,Muhammad Iqbal,Alagan Anpalagan,Ayaz Ahmad,Mohammad S. Obaidat +5 more
TL;DR: In this paper, the authors present a general optimization framework for WSNs in smart grid and specify different possibilities for input, output, objective function, and constraints, and investigate different objectives used in defining the optimization problems.
Proceedings ArticleDOI
An alternative method for multiarea state estimation based on OCD
TL;DR: In this paper, an alternative method for multi-area state estimation based on Optimality Condition Decomposition (OCD) is proposed to solve the problem of state estimation in a decentralized optimization scheme with minimum information exchange among subsystems.
References
More filters
Parallel and distributed computation
TL;DR: This book focuses on numerical algorithms suited for parallelization for solving systems of equations and optimization problems, with emphasis on relaxation methods of the Jacobi and Gauss-Seidel type.
Journal ArticleDOI
Distributed Stochastic Subgradient Projection Algorithms for Convex Optimization
TL;DR: This paper considers a distributed multi-agent network system where the goal is to minimize a sum of convex objective functions of the agents subject to a common convex constraint set, and investigates the effects of stochastic subgradient errors on the convergence of the algorithm.
Journal ArticleDOI
Consensus in Ad Hoc WSNs With Noisy Links— Part I: Distributed Estimation of Deterministic Signals
TL;DR: This work introduces a decentralized scheme for least-squares and best linear unbiased estimation (BLUE) and establishes its convergence in the presence of communication noise and introduces a method of multipliers in conjunction with a block coordinate descent approach to demonstrate how the resultant algorithm can be decomposed into a set of simpler tasks suitable for distributed implementation.
Journal ArticleDOI
Distributed Consensus Algorithms in Sensor Networks: Quantized Data and Random Link Failures
Soummya Kar,Jose M. F. Moura +1 more
TL;DR: In this article, the authors studied the problem of distributed average consensus in sensor networks with quantized data and random link failures. But their work was restricted to the case where the quantizer range is unbounded.
Related Papers (5)
On distributed optimization under inequality and equality constraints via penalty primal-dual methods
Minghui Zhu,Sonia Martinez +1 more