Geometric programming: Difference between revisions

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=== To solve a standard form Geometric Programming problem ===
=== To solve a standard form Geometric Programming problem ===
'''Minimize''' <math>f_0( </math>
'''Minimize''' <math>f_0(x,y) = x^2y^3 + 3x + 2xy </math>


'''Subject to:''' <math>f_i(x)\leqslant1 </math>,    <math>i </math> = 1,...,m,
'''Subject to:''' <math>f_i(x)\leqslant1 </math>,    <math>i </math> = 1,...,m,

Revision as of 16:45, 13 November 2021

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

Subject to: , = 1,...,m,

, = 1,...,p,

, = 1,...,q,

where are posynomial functions, are monomials, and are the optimization variables.



Numerical Examples

To solve a standard form Geometric Programming problem

Minimize

Subject to: , = 1,...,m,

, = 1,...,p,

, = 1,...,q,


Applications

Conclusion

References