On the relation between flexibility analysis and robust optimization for linear systems

Qi Zhang, Ignacio E. Grossmann, Ricardo Lima

Research output: Contribution to journalArticlepeer-review

64 Scopus citations


Flexibility analysis and robust optimization are two approaches to solving optimization problems under uncertainty that share some fundamental concepts, such as the use of polyhedral uncertainty sets and the worst-case approach to guarantee feasibility. The connection between these two approaches has not been sufficiently acknowledged and examined in the literature. In this context, the contributions of this work are fourfold: (1) a comparison between flexibility analysis and robust optimization from a historical perspective is presented; (2) for linear systems, new formulations for the three classical flexibility analysis problems—flexibility test, flexibility index, and design under uncertainty—based on duality theory and the affinely adjustable robust optimization (AARO) approach are proposed; (3) the AARO approach is shown to be generally more restrictive such that it may lead to overly conservative solutions; (4) numerical examples show the improved computational performance from the proposed formulations compared to the traditional flexibility analysis models. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3109–3123, 2016
Original languageEnglish (US)
Pages (from-to)3109-3123
Number of pages15
JournalAIChE Journal
Issue number9
StatePublished - May 31 2016

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The authors gratefully acknowledge the financial support from the National Science Foundation under Grant No. 1159443.


Dive into the research topics of 'On the relation between flexibility analysis and robust optimization for linear systems'. Together they form a unique fingerprint.

Cite this