Acta Oeconomica Pragensia 2005, 13(1):128-134 | DOI: 10.18267/j.aop.145

Using Metrics in Stability of Stochastic Programming Problems

Michal Houda
Mgr. Michal Houda - student of doctoral study; Department of Probability and Mathematical Statistics, Faculty of Mathematics and Physics, Charles University in Prague, Ke Karlovu 3, 121 16 Prague 2, houda@karlin.mff.cuni.cz

Optimization techniques enter often as a mathematical tool into many economic applications. In these models, uncertainty is modelled via probability distribution that is approximated or estimated in real cases. Then we ask for a stability of solutions with respect to changes in the probability distribution. The work illustrates one of possible approaches (using probability metrics), underlying numerical challenges and a backward glance to economical interpretation.

Keywords: stochastic programming, quantitative stability, Wasserstein metrics, Kolmogorov metrics, simulation study
JEL classification: C44

Published: March 1, 2005  Show citation

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Houda, M. (2005). Using Metrics in Stability of Stochastic Programming Problems. Acta Oeconomica Pragensia, 13(1), 128-134. doi: 10.18267/j.aop.145
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