8,441 research outputs found
A Practical Guide to Robust Optimization
Robust optimization is a young and active research field that has been mainly
developed in the last 15 years. Robust optimization is very useful for
practice, since it is tailored to the information at hand, and it leads to
computationally tractable formulations. It is therefore remarkable that
real-life applications of robust optimization are still lagging behind; there
is much more potential for real-life applications than has been exploited
hitherto. The aim of this paper is to help practitioners to understand robust
optimization and to successfully apply it in practice. We provide a brief
introduction to robust optimization, and also describe important do's and
don'ts for using it in practice. We use many small examples to illustrate our
discussions
Theory and Applications of Robust Optimization
In this paper we survey the primary research, both theoretical and applied,
in the area of Robust Optimization (RO). Our focus is on the computational
attractiveness of RO approaches, as well as the modeling power and broad
applicability of the methodology. In addition to surveying prominent
theoretical results of RO, we also present some recent results linking RO to
adaptable models for multi-stage decision-making problems. Finally, we
highlight applications of RO across a wide spectrum of domains, including
finance, statistics, learning, and various areas of engineering.Comment: 50 page
Finite Alphabet Control of Logistic Networks with Discrete Uncertainty
We consider logistic networks in which the control and disturbance inputs
take values in finite sets. We derive a necessary and sufficient condition for
the existence of robustly control invariant (hyperbox) sets. We show that a
stronger version of this condition is sufficient to guarantee robust global
attractivity, and we construct a counterexample demonstrating that it is not
necessary. Being constructive, our proofs of sufficiency allow us to extract
the corresponding robust control laws and to establish the invariance of
certain sets. Finally, we highlight parallels between our results and existing
results in the literature, and we conclude our study with two simple
illustrative examples
Mathematical control of complex systems
Copyright © 2013 ZidongWang et al.This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
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