Algorithm 883
- 25 July 2008
- journal article
- research article
- Published by Association for Computing Machinery (ACM) in ACM Transactions on Mathematical Software
- Vol. 35 (2), 1-13
- https://doi.org/10.1145/1377612.1377619
Abstract
SparsePOP is a Matlab implementation of the sparse semidefinite programming (SDP) relaxation method for approximating a global optimal solution of a polynomial optimization problem (POP) proposed by Waki et al. [2006]. The sparse SDP relaxation exploits a sparse structure of polynomials in POPs when applying “a hierarchy of LMI relaxations of increasing dimensions” Lasserre [2006]. The efficiency of SparsePOP to approximate optimal solutions of POPs is thus increased, and larger-scale POPs can be handled.Keywords
Funding Information
- Korea Science and Engineering Foundation (R01-2005-000-10271-0)
- Japan Society for the Promotion of Science (16016234, 19310096, 15740054)
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