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01662 am a22002413u 4500 |
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87686 |
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|a Bertsimas, Dimitris J.
|e author
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|a Sloan School of Management
|e contributor
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|a Bertsimas, Dimitris J.
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|a Freund, Robert Michael
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|a Freund, Robert Michael
|e author
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|a Sun, Xu Andy
|e author
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|a An accelerated first-order method for solving SOS relaxations of unconstrained polynomial optimization problems
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|b Taylor & Francis,
|c 2014-06-06T17:27:23Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/87686
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|a Our interest lies in solving sum of squares (SOS) relaxations of large-scale unconstrained polynomial optimization problems. Because interior-point methods for solving these problems are severely limited by the large-scale, we are motivated to explore efficient implementations of an accelerated first-order method to solve this class of problems. By exploiting special structural properties of this problem class, we greatly reduce the computational cost of the first-order method at each iteration. We report promising computational results as well as a curious observation about the behaviour of the first-order method for the SOS relaxations of the unconstrained polynomial optimization problem.
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|a United States. Air Force Office of Scientific Research (Grant No. FA9550-08-1-0350)
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|a United States. Air Force Office of Scientific Research (AFOSR Grant No. FA9550-11-1-0141)
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|a Singapore-MIT Alliance
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|a en_US
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|a Article
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|t Optimization Methods and Software
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