A study on distributed optimization over large-scale networked systems
type: Item
instance of: scholarly article
title: A study on distributed optimization over large-scale networked systems
zbMATH Open document ID: 1477.90057
DOI: 10.1155/2021/5540262
author: Hansi K. Abeynanda
author: G. H. J. Lanel
published in: Journal of Mathematics
publication date: 2021-06-28T00:00:00Z
review text: Summary: Distributed optimization is a very important concept with applications in control theory and many related fields, as it is high fault-tolerant and extremely scalable compared with centralized optimization. Centralized solution methods are not suitable for many application domains that consist of large number of networked systems. In general, these large-scale networked systems cooperatively find an optimal solution to a common global objective during the optimization process. Thus, it gives us an opportunity to analyze distributed optimization techniques that is demanded in most distributed optimization settings. This paper presents an analysis that provides an overview of decomposition methods as well as currently existing distributed methods and techniques that are employed in large-scale networked systems. A detailed analysis on gradient like methods, subgradient methods, and methods of multipliers including the alternating direction method of multipliers is presented. These methods are analyzed empirically by using numerical examples. Moreover, an example highlighting the fact that the gradient method fails to solve distributed problems in some circumstances is discussed under numerical results. A numerical implementation is used to demonstrate that the alternating direction method of multipliers can solve this particular problem, by revealing its robustness compared with the gradient method. Finally, we conclude the paper with possible future research directions.
Mathematics Subject Classification ID: 90C25
Mathematics Subject Classification ID: 90C30
Mathematics Subject Classification ID: 65K05
zbMATH DE Number: 7363794
describes a project that uses: PDCO
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2021/5540262
OpenAlex ID: W3159235436
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description: scientific article; zbMATH DE number 7363794