Robust Geometric Programming is co-NP hard

Chassein, André and Goerigk, Marc (2014) Robust Geometric Programming is co-NP hard. Working Paper. UNSPECIFIED.

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Abstract

Geometric Programming is a useful tool with a wide range of applications in engineering. As in real-world problems input data is likely to be affected by uncertainty, Hsiung, Kim, and Boyd introduced robust geometric programming to include the uncertainty in the optimization process. They also developed a tractable approximation method to tackle this problem. Further, they pose the question whether there exists a tractable reformulation of their robust geometric programming model instead of only an approximation method. We give a negative answer to this question by showing that robust geometric programming is co-NP hard in its natural posynomial form.

Item Type: Monograph (Working Paper)
Departments: Lancaster University Management School > Management Science
ID Code: 86065
Deposited By: ep_importer_pure
Deposited On: 27 Apr 2017 12:40
Refereed?: No
Published?: Published
Last Modified: 24 Jan 2020 05:04
URI: https://eprints.lancs.ac.uk/id/eprint/86065

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