NDLI: Distributed continuous-time optimization based on Lagrangian functions

Content Provider	IEEE Xplore Digital Library
Author	Lu Cao Weisheng Chen
Copyright Year	2014
Description	Author affiliation: Sch. of Math. & Stat., Xidian Univ., Xian, China (Lu Cao; Weisheng Chen)
Abstract	Distributed optimization is an emerging research topic. Agents in the network solve the problem by exchanging information which depicts people's consideration on a optimization problem in real lives. In this paper, we introduce two algorithms in continuous-time to solve distributed optimization problems with equality constraints where the cost function is expressed as a sum of functions and where each function is associated to an agent. We firstly construct a continuous dynamic system by utilizing the Lagrangian function and then show that the algorithm is locally convergent and globally stable under certain conditions. Then, we modify the Lagrangian function and re-construct the dynamic system to prove that the new algorithm will be convergent under more relaxed conditions. At last, we present some simulations to prove our theoretical results.
Starting Page	5796
Ending Page	5801
File Size	245626
Page Count	6
File Format	PDF
ISBN	9789881563873
ISSN	19341768
DOI	10.1109/ChiCC.2014.6895931
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	TCCT, CAA
Subject Keyword	Heuristic algorithms Constrained Optimization Lagrangian Function Linear programming Distributed Optimization Eigenvalues and eigenfunctions Vectors Continuous-Time Optimization Equations Lagrangian functions
Content Type	Text
Resource Type	Article

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