文章基本信息

标题：A Duality-Based Approach for Distributed Optimization with Coupling Constraints
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作者：Ivano Notarnicola ; Giuseppe Notarstefano
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2017
卷号：50
期号：1
页码：14326-14331
DOI：10.1016/j.ifacol.2017.08.1874
语种：English
出版社：Elsevier
摘要：AbstractIn this paper we consider a distributed optimization scenario in which a set of agents has to solve a convex optimization problem with separable cost function, local constraint sets and a coupling inequality constraint. We propose a novel distributed algorithm based on a relaxation of the primal problem and an elegant exploration of duality theory. Despite its complex derivation based on several duality steps, the distributed algorithm has a very simple and intuitive structure. That is, each node solves a local version of the original problem relaxation, and updates suitable dual variables. We prove the algorithm correctness and show its effectiveness via numerical computations.
关键词：KeywordsOptimizationcontrol of large-scale network systemsLarge scale optimization problemsCyber-Physical SystemsConvex optimizationDistributed controlestimation