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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 ...
On discounted stochastic games with incomplete information on payoffs and a security application
This paper presents a robust optimization model for n-person finite state/action stochastic games with incomplete information on payoffs. For polytopic uncertainty sets, we propose an explicit mathematical programming ...
A survey of adjustable robust optimization
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 dual response optimization
(Taylor & Francis, 2016)
This article presents a robust optimization reformulation of the dual response problem developed in response surface methodology. The dual response approach fits separate models for the mean and the variance, and analyzes ...
A robust optimization approach for humanitarian needs assessment planning under travel time uncertainty
We focus on rapid needs assessment operations conducted immediately after a disaster to identify the urgent needs of the affected community groups, and address the problem of selecting the sites to be visited by the ...
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