Linear Convergence of First- and Zeroth-Order Primal-Dual Algorithms for Distributed Nonconvex Optimization

This article considers the distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of local cost functions by using local information exchange. We first consider a distributed first-order primal-dual algorithm. We show that it converges sublinearly to a statio...

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Vydané v:	IEEE transactions on automatic control Ročník 67; číslo 8; s. 4194 - 4201
Hlavní autori:	Yi, Xinlei, Zhang, Shengjun, Yang, Tao, Chai, Tianyou, Johansson, Karl H.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.08.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Convergence Convex functions Convexity Cost function Costs Distributed nonconvex optimization First order algorithms first-order algorithm Laplace equations linear convergence Lyapunov methods Optimization primal-dual algorithm Technological innovation zeroth-order algorithm zerothorder algorithm
ISSN:	0018-9286, 1558-2523, 1558-2523
On-line prístup:	Získať plný text
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