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Description:: In this thesis we discuss the issue of solving stochastic optimization problems using sampling methods. Numerical results have shown that using variance reduction techniques from statistics can result in significant improvements over Monte Carlo sampling in terms of the number of samples needed for convergence of the optimal objective value...
Keyword:: Stochastic Programming, Quasi-Monte Carlo, Padding, Latin Hypercube, Large Deviations, and QMC
Subject:: Industrial Engineering and Management Sciences
Creator:: Shane Sebastian Drew
Owner:: Scholarly Digital Publishing
Date Uploaded:: 08/27/2018
Date Modified:: 08/27/2018
Date Created:: 2007-12-05
Resource Type:: Dissertation

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