DTIC ADA278654: Stopping Rules For A Class Of Sampling-Based Stochastic Programming Algorithms - Info and Reading Options
By Defense Technical Information Center
"DTIC ADA278654: Stopping Rules For A Class Of Sampling-Based Stochastic Programming Algorithms" and the language of the book is English.
“DTIC ADA278654: Stopping Rules For A Class Of Sampling-Based Stochastic Programming Algorithms” Metadata:
- Title: ➤ DTIC ADA278654: Stopping Rules For A Class Of Sampling-Based Stochastic Programming Algorithms
- Author: ➤ Defense Technical Information Center
- Language: English
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- Internet Archive ID: DTIC_ADA278654
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"DTIC ADA278654: Stopping Rules For A Class Of Sampling-Based Stochastic Programming Algorithms" Description:
The Internet Archive:
Decomposition and Monte Carlo sampling-based algorithms hold much promise for solving stochastic programs with many scenarios. A critical component of such algorithms is a stopping criterion to ensure the quality of the solution. In this paper, we develop a stopping rule theory for a class of algorithms that estimate bounds on the optimal objective function value by sampling. We provide rules for selecting sample sizes and terminating the algorithm under which asymptotic validity of confidence intervals for the quality of the proposed solution can be verified. These rules are applied to a multistage stochastic linear programming algorithm due to Pereira and Pinto.
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