Distributed Algorithms for Robust Convex Optimization via the Scenario Approach

This paper proposes distributed algorithms to solve robust convex optimization (RCO) when the constraints are affected by nonlinear uncertainty. We adopt a scenario approach by randomly sampling the uncertainty set. To facilitate the computational task, instead of using a single centralized processo...

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Veröffentlicht in:	IEEE transactions on automatic control Jg. 64; H. 3; S. 880 - 895
Hauptverfasser:	You, Keyou, Tempo, Roberto, Xie, Pei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.03.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Computational efficiency Computational geometry Convex analysis Convex functions Convexity Distributed algorithms Graph theory Linear programming Microprocessors Optimization Primal-dual algorithm Processors random projection algorithm robust convex optimization (RCO) Robustness scenario approach System identification Uncertainty
ISSN:	0018-9286, 1558-2523
Online-Zugang:	Volltext
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