SparsePOP
swMATH ID: | 4331 |
Software Authors: | Waki, Hayato; Kim, Sunyoung; Kojima, Masakazu; Muramatsu, Masakazu; Sugimoto, Hiroshi |
Description: | SparsePOP: a sparse semidefinite programming relaxation of polynomial optimization problems. 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. |
Homepage: | http://sourceforge.net/projects/sparsepop/ |
Source Code: | https://github.com/robertgj/SparsePOP |
Dependencies: | Matlab |
Related Software: | SeDuMi; GloptiPoly; SDPT3; SDPA; YALMIP; Sostools; Mosek; Matlab; SFSDP; SPOTless; CSDP; TSSOS; minpack; Benchmarks for Optimization Software; Sparse-BSOS; BARON; NCSOStools; SDPLIB; JuMP; LightGraphs.jl |
Cited in: | 72 Documents |
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Cited by 101 Authors
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