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A survey of adjustable robust optimization
(Elsevier, 2019-09)
Static robust optimization (RO) is a methodology to solve mathematical optimization problems with uncertain data. The objective of static RO is to find solutions that are immune to all perturbations of the data in a so-called ...
Robust reformulations of ambiguous chance constraints with discrete probability distributions
(Balikesir University, 2019)
This paper proposes robust reformulations of ambiguous chance constraints when the underlying family of distributions is discrete and supported in a so-called ``p-box'' or ``p-ellipsoidal'' uncertainty set. Using the robust ...
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