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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  2. Xu, Gongxian: Global optimization of signomial geometric programming problems (2014)
  3. Li, Yiming; Chen, Ying-Chieh: Geometric programming approach to doping profile design optimization of metal-oxide-semiconductor devices (2013)
  4. Lim, Johan; Won, Joong-Ho: ROC convex hull and nonparametric maximum likelihood estimation (2012)
  5. Aizik, Yoni; Kolodny, Avinoam: Finding the energy efficient curve: gate sizing for minimum power under delay constraints (2011)
  6. Lee, Kyeong Eun; Lim, Johan: Nonparametric maximum likelihood estimation of a concave receiver operating characteristic curve via geometric programming (2011)
  7. Chen, Ying-Chieh; Li, Yiming: Temperature-aware floorplanning via geometric programming (2010)
  8. Vera, Julio; González-Alcón, Carlos; Marín-Sanguino, Alberto; Torres, Néstor: Optimization of biochemical systems through mathematical programming: methods and applications (2010)
  9. Lim, Johan; Wang, Xinlei; Choi, Wanseok: Maximum likelihood estimation of ordered multinomial probabilities by geometric programming (2009)
  10. Boyd, Stephen; Kim, Seung-Jean; Vandenberghe, Lieven; Hassibi, Arash: A tutorial on geometric programming (2007)
  11. Kim, Seung-Jean; Boyd, Stephen P.; Yun, Sunghee; Patil, Dinesh D.; Horowitz, Mark A.: A heuristic for optimizing stochastic activity networks with applications to statistical digital circuit sizing (2007)
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