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 15:45, 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,