期刊
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
卷 42, 期 1, 页码 31-41出版社
SPRINGER
DOI: 10.1007/s10589-007-9112-2
关键词
Polynomial optimization problem; Conic program; Symmetric cone; Euclidean Jordan algebra; Sum of squares; Global optimization; Semidefinite program
资金
- Grant-in-Aid for Scientific Research on Priority Areas [16016234]
- Grant-in-Aid for Young Scientists [15740054]
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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