GGPLAB
GGPLAB is a Matlab-based toolbox for specifying and solving geometric programs (GPs) and generalized geometric programs (GGPs). It is intended to complement the survey paper A Tutorial on Geometric Programming, and the book Convex Optimization.GGPLAB consists ofGPCVX, a primal-dual interior-point solver for GP (in convex form) and a wrapper, GPPOSY, that accepts GPs in posynomial form.A library of objects, such as monomials, posynomials, and generalized posynomials, to support the specification of GPs and GGPs.A variety of examples.Some caveats:The convex optimization toolbox CVX now supports GP. We recommend CVX for large or complex problems; we recommend GGPLAB, on the other hand, for learning the basics of GP.The solver GPCVX supports sparse problems, but is not designed for very large scale problems.Object manipulation overhead can make GGPLAB slow on larger problems.GGPLAB does not support dual variables. (The solver GPCVX, however, does.)
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References in zbMATH (referenced in 13 articles )
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- Lee, Kyeong Eun; Lim, Johan: Nonparametric maximum likelihood estimation of a concave receiver operating characteristic curve via geometric programming (2011)
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- Lim, Johan; Wang, Xinlei; Choi, Wanseok: Maximum likelihood estimation of ordered multinomial probabilities by geometric programming (2009)
- Boyd, Stephen; Kim, Seung-Jean; Vandenberghe, Lieven; Hassibi, Arash: A tutorial on geometric programming (2007)
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- Peterson, Elmor L.: Geometric programming (1976)