On polyhedral and second-order cone decompositions of semidefinite optimization problems
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1910.03143.pdf
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Accepted version
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Author(s) •
Bertsimas, Dimitris J
Cory-Wright, Ryan
Date Issued
January 2020
Journal
Operations Research Letters
Publisher
Elsevier BV
Citation
Bertsimas, Dimitris and Ryan Cory-Wright. "On polyhedral and second-order cone decompositions of semidefinite optimization problems." Operations Research Letters 48, 1 (January 2020): 78-85
Version
Author's final manuscript
Abstract
We study a cutting-plane method for semidefinite optimization problems, and supply a proof of the method's convergence, under a boundedness assumption. By relating the method's rate of convergence to an initial outer approximation's diameter, we argue the method performs well when initialized with a second-order cone approximation, instead of a linear approximation. We invoke the method to provide bound gaps of 0.5–6.5% for sparse PCA problems with 1000s of covariates, and solve nuclear norm problems over 500 × 500 matrices.
MIT Department
Sloan School of Management
Massachusetts Institute of Technology. Operations Research Center
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1016/j.orl.2019.12.003