Geometric measures of convex sets and bounds on problem sensitivity and robustness for conic linear optimization

The effect of data perturbation and uncertainty has always been an important consideration in Optimization. It is important to know whether a given problem is very sensible to perturbations on the data or, on the contrary, is more “robust”. Problem geometry does have an impact on the sensitivity of...

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Vydané v:	Mathematical programming Ročník 147; číslo 1-2; s. 47 - 79
Hlavný autor:	Vera, Jorge R.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2014 Springer Nature B.V
Predmet:	Analysis Calculus of Variations and Optimal Control; Optimization Combinatorics Computer science Conics Convex analysis Estimates Full Length Paper Geometry Impact analysis Joints Linear programming Mathematical and Computational Physics Mathematical Methods in Physics Mathematical programming Mathematics Mathematics and Statistics Mathematics of Computing Numerical Analysis Optimization Perturbation methods Robustness Sensitivity analysis Studies Theoretical Uncertainty 90C31 90C05 90C25 Geometric measures Conic optimization Sensitivity and stability in optimization
ISSN:	0025-5610, 1436-4646
On-line prístup:	Získať plný text
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