National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Stochastic Optimization on Random Networks
Sigačevová, Jana ; Houda, Michal (advisor) ; Branda, Martin (referee)
The deterministic theory of graphs and networks is used successfully in cases where no random component is needed. However in practice, a number of decision-making and conflict situations require the inclusion of a stochastic element directly into the model. The objective of this thesis is the introduction of stochastic optimization and its application on random networks. The reader will become familiar with three approaches to stochastic optimization. Namely two-stage optimization, multi-stage optimization and chance constraint optimization. Finally, the studied issue is demonstrated on a real telecommunication network example.
Stochastic networks
Sigačevová, Jana ; Lachout, Petr (advisor) ; Hlubinka, Daniel (referee)
It is possible to simulate a lot of real decision-making and conflict situations by random weighted graph which we can control. It is important to find the optimal solution with respect to the given criteria. The objective of this thesis is to present multicriteria optimization and multicriteria stochastic optimization. Further, the reader becomes familiar with three examples of problems leading to control stochastic networks. We present a minimization of a stochastic maximum-reliability path, minimization of investment cost and the rejection costs and thirdly combination of stochastic programming and Markov decision process. Finally we present the application of multicriteria optimization on an example. Powered by TCPDF (www.tcpdf.org)

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