Geometric programming

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

Introduction

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)\leqslant1 $, $ 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)\leqslant1 $, $ i $ = 1,...,m,

$ g_i(x) = 1 $, $ i $ = 1,...,p,

$ x_i > 0 $, $ i $ = 1,...,q,


Applications

Conclusion

References