Journal of Global Optimization

, Volume 41, Issue 4, pp 593–612

A robust algorithm for generalized geometric programming

Article

DOI: 10.1007/s10898-008-9283-0

Cite this article as:
Shen, P., Ma, Y. & Chen, Y. J Glob Optim (2008) 41: 593. doi:10.1007/s10898-008-9283-0

Abstract

Most existing methods of global optimization for generalized geometric programming (GGP) actually compute an approximate optimal solution of a linear or convex relaxation of the original problem. However, these approaches may sometimes provide an infeasible solution, or far from the true optimum. To overcome these limitations, a robust solution algorithm is proposed for global optimization of (GGP) problem. This algorithm guarantees adequately to obtain a robust optimal solution, which is feasible and close to the actual optimal solution, and is also stable under small perturbations of the constraints.

Keywords

Generalized geometric programming Robust solution Global optimization Essential optimal solution Monotonic optimization 

Copyright information

© Springer Science+Business Media, LLC. 2008

Authors and Affiliations

  1. 1.College of Mathematics and Information ScienceHenan Normal UniversityXinxiangP.R.China

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