Journal
OPTIMIZATION METHODS & SOFTWARE
Volume 31, Issue 2, Pages 405-434Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/10556788.2015.1121489
Keywords
global polynomial optimization; semidefinite programming relaxations; linear matrixinequalities; polynomial matrix inequalities; 90C26; 90C22
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Funding
- EC [FP7-SPACE-2012-312377 PRoViDE]
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Global polynomial optimization can be a powerful tool when applied to engineering problems. One of the most successful methods for solving such problems is based on convex linear matrix inequality (LMI) relaxations. Software implementations of this approach can be found for example in Matlab toolboxes GloptiPoly and YALMIP. Matlab language makes it very easy when it comes to modelling polynomial problems. However, when using these toolboxes, Matlab is also required for the problem solving. GpoSolver aims at bridging this gap by providing a Matlab-based problem modelling toolbox supplemented by a problem-solving back end in a form of a C++ template library. Once a problem is conveniently modelled and parametrized in Matlab, a C++ class is automatically generated by GpoSolver. This class can be easily included into an existing codebase and used to solve different instances of the problem based on the supplied parameters.
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