Probabilistic constrained optimization on flow networks

HIGHLIGHTS

• who: Michael Schuster from the Department of Mathematics, Friedrich-Alexander University Erlangen-Nürnberg, Cauerstrasse, Erlangen, Germany have published the research: Probabilistic constrained optimization on flow networks, in the Journal: (JOURNAL)
• what: The aim of this paper is to solve probabilistic constrained optimization problems and to derive necessary optimality conditions for them in the context of flow networks. The authors compare both results in a numerical computation with a classical Monte Carlo method (All numerical tests have been done with MATLABⓇ, version 2015a). Next the authors use both methods, the SRD and the KDE, to . . .
  

   

  

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