Sequential Randomized Algorithms for Convex Optimization in the Presence of Uncertainty

In this paper, we propose new sequential randomized algorithms for convex optimization problems in the presence of uncertainty. A rigorous analysis of the theoretical properties of the solutions obtained by these algorithms, for full constraint satisfaction and partial constraint satisfaction, respe...

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Veröffentlicht in:	arXiv.org 2015-09
Hauptverfasser:	Chamanbaz, Mohammadreza, Dabbene, Fabrizio, Tempo, Roberto, Venkatakrishnan Venkataramanan, Qing-Guo, Wang
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Computational geometry Computer Science - Systems and Control Computer simulation Convex analysis Convexity Disk drives Mathematics - Optimization and Control Optimization Randomization Randomized algorithms Uncertainty analysis
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