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Quasi-Monte Carlo Methods for Stochastic Programming

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