Solving Static and Dynamic Stochastic Optimization Problem Via Sparse Grid and Interior Point Methods and Complexity Analysis

Solving Static and Dynamic Stochastic Optimization Problem Via Sparse Grid and Interior Point Methods and Complexity Analysis

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Secondly, we consider how to approximate a stochastic problem with continuous distribution by generating scenarios. We propose sparse grid method for the purpose of generating scenarios. As with any approximations, we analyze the error bounds of the proposed methods and prove its epi-convergent property. We also show numerically that the proposed method converges to the true optimal value fast in comparison with Monte Carlo and Quasi Monte Carlo methods.We assume that the set G has a non-empty relative interior, and the sets Gk, k = 1 , ..., K, have a non-empty relative interior for any x that is in the relative interior of G (complete recourse). L and Lk, k = 1, ..., K, represent affine spaces, i.e., L a‰i {xanbsp;...


Title:Solving Static and Dynamic Stochastic Optimization Problem Via Sparse Grid and Interior Point Methods and Complexity Analysis
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Publisher:ProQuest - 2008
ISBN-13:

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