Geometric programming
From Wikipedia, the free encyclopedia
A Geometric Program is an optimization problem of the form
minimize subject to
where are posynomials and are monomials. It should be noted that in the context of geometric programming (unlike all other disciplines), a monomial is defined as a function with defined as
where and .
GPs have numerous application, such as circuit sizing and parameter estimation via logistic regression in statistics. The maximum likelihood estimator in logistic regression is a GP.
[edit] Convex form
Geometric programs are not (in general) convex optimization problems, but they can be transformed to convex problems by a change of variables and a transformation of the objective and constraint functions. In particular, defining yi = logxi, the monomial , where b = logc. Similarly, if f is the posynomial
then , where and bk = logck. After the change of variables, a posynomial becomes a sum of exponentials of affine functions.
[edit] External links
- S. Boyd, S. J. Kim, L. Vandenberghe, and A. Hassibi, A Tutorial on Geometric Programming
- S. Boyd, S. J. Kim, D. Patil, and M. Horowitz Digital Circuit Optimization via Geometric Programming