Extending scope of robust optimization: comprehensive robust counterparts of uncertain problems. (English) Zbl 1134.90042

Summary: In this paper, we propose a new methodology for handling optimization problems with uncertain data. With the usual robust optimization paradigm, one looks for the decisions ensuring a required performance for all realizations of the data from a given bounded uncertainty set, whereas with the proposed approach, we require also a controlled deterioration in performance when the data is outside the uncertainty set.
The extension of robust optimization methodology developed in this paper opens up new possibilities to solve efficiently multi-stage finite-horizon uncertain optimization problems, in particular, to analyze and to synthesize linear controllers for discrete time dynamical systems.


90C31 Sensitivity, stability, parametric optimization
90C05 Linear programming
90C25 Convex programming
90C34 Semi-infinite programming
93C55 Discrete-time control/observation systems
Full Text: DOI


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