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Conic Geometric Programming

Chandrasekaran, Venkat and Shah, Parikshit (2014) Conic Geometric Programming. In: 48th Annual Conference on Information Sciences and Systems. IEEE , Piscataway, NJ, pp. 1-4. ISBN 978-1-4799-3001-2.

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This invited submission summarizes recent work by the authors on conic geometric programs (CGPs), which are convex optimization problems obtained by blending geometric programs (GPs) and conic optimization problems such as semidefinite programs (SDPs). GPs and SDPs are two prominent families of structured convex programs that each generalize linear programs (LPs) in different ways, and that are both employed in a broad range of applications. This submission provides a summary of a unified mathematical and algorithmic treatment of GPs and SDPs under the framework of CGPs. Although CGPs contain GPs and SDPs as special instances, computing global optima of CGPs is not much harder than solving GPs and SDPs. More broadly, the CGP framework facilitates a range of new applications – permanent maximization, hitting-time estimation in dynamical systems, the computation of the capacity of channels transmitting quantum information, and robust optimization formulations of GPs – that fall outside the scope of SDPs and GPs alone.

Item Type:Book Section
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Additional Information:© 2014 IEEE.
Record Number:CaltechAUTHORS:20150430-092047133
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Official Citation:Chandrasekaran, V.; Shah, P., "Conic geometric programming," Information Sciences and Systems (CISS), 2014 48th Annual Conference on , vol., no., pp.1,4, 19-21 March 2014 doi: 10.1109/CISS.2014.6814151 URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:57108
Deposited By: Tony Diaz
Deposited On:30 Apr 2015 20:14
Last Modified:03 Oct 2019 08:21

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