Geometric programming

Authors: Wenjun Zhu(wz274), Sam Olsen(sgo23) (SYSEN5800, FALL 2021)

Theory/Methodology

Definition

The standard form of Geometric Programming optimization is to minimize the objective function which must be posynomial. The inequality constraints can only have the form of a posynomial less than or equal to one, and the equality constraints can only have the form of a monomial equal to one.

Standard Form

Minimize $f_{0}(x)$

Subject to: $f_{i}(x)\leqslant 1$, $i$ = 1,...,m,

$g_{i}(x)=1$, $i$ = 1,...,p,

$x_{i}>0$, $i$ = 1,...,q,

where $f_{i}(x)$ are posynomial functions, $g_{i}(x)$ are monomials, and $x_{i}$ are the optimization variables.

Numerical Examples

To solve a standard form Geometric Programming problem

Minimize $f_{0}($

Subject to: $f_{i}(x)\leqslant 1$, $i$ = 1,...,m,

$g_{i}(x)=1$, $i$ = 1,...,p,

$x_{i}>0$, $i$ = 1,...,q,