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What is Uncertainty Set

Chapter 2
Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics
This is one of the basic input data which is required to specify an optimization problem under uncertainty on some of the parameters such as coefficients in the constraints or in the objective function. Given p uncertain real parameters, the uncertainty set (in p-dimensional real space) is the set of values which can possibly be taken by the p parameters considered. This set may feature finite cardinality, or may contain infinitely many elements (compactness being assumed in this case) .
Published in Chapter:
Robust Two-Stage and Multistage Optimization: Complexity Issues and Applications
Michel Andre Minoux (University P. and M. Curie, France)
Copyright: © 2016 |Pages: 41
DOI: 10.4018/978-1-4666-9644-0.ch002
Abstract
This chapter is intended as an overview of robust optimization models related to optimization problems subject to uncertain data, with special focus on the case when uncertainty impacts the right-hand side coefficients in the constraints. Two-stage as well as multistage models are addressed, emphasizing links with applications and computational complexity issues. A class of multistage robust optimization problems for which exact optimal strategies can be efficiently computed (via a robust dynamic programming recursion) is discussed. An application to a multiperiod energy production planning problem is presented into detail, and computational results are reported.
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