Geometric programs treated with slack variables +

Abstract

Kochenberger and Woolsey have introduced slack variables into the constraints of a geometric program and have added their reciprocals to the objective function. They find this augmented program advantageous for numerical minimization. In this paper the augmented program is used to give a relatively simple proof of the "refined duality theory" of geometric programming. This proof also shows that the optimal solutions for the augmented program converge to the (desired) optimal solutions for the original program as certain parameters approach zero