Journal
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
Volume 42, Issue 1, Pages 31-41Publisher
SPRINGER
DOI: 10.1007/s10589-007-9112-2
Keywords
Polynomial optimization problem; Conic program; Symmetric cone; Euclidean Jordan algebra; Sum of squares; Global optimization; Semidefinite program
Funding
- Grant-in-Aid for Scientific Research on Priority Areas [16016234]
- Grant-in-Aid for Young Scientists [15740054]
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This short note extends the sparse SOS (sum of squares) and SDP (semidefinite programming) relaxation proposed by Waki, Kim, Kojima and Muramatsu for normal POPs (polynomial optimization problems) to POPs over symmetric cones, and establishes its theoretical convergence based on the recent convergence result by Lasserre on the sparse SOS and SDP relaxation for normal POPs. A numerical example is also given to exhibit its high potential.
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