Stochastic optimization on Bayesian nets
Article Abstract:
An a posteriori gradient estimation scheme based on Gibbs sampler is used in a Bayesian net approach for defining and solving a stochastic optimization problem. The use of the Bayesian net approach allows for the description of joint probability distributions in the optimization model while the Gibbs sampler allows for gradient estimation when random variables are discrete. A validation of the model in a semiconductor environment proved the robustness of the technique.
Publication Name: European Journal of Operational Research
Subject: Business, international
ISSN: 0377-2217
Year: 1997
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The role of the augmented system in interior point methods
Article Abstract:
Improvements in the pivot point search heuristics were shown to be effective in increasing the utility of the augmented system approach in interior point methods. Improvement in the pivot point search makes the algorithm competitive with the conventional normal equation method used throughout the industry, such as the AD-1 AT method. The augmented system is especially useful in large problems where both the AD-1 AT is dense as well as the Cholesky factor.
Publication Name: European Journal of Operational Research
Subject: Business, international
ISSN: 0377-2217
Year: 1998
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The augmented system variant of IPMs in two-stage stochastic linear programming computation
Article Abstract:
The augmented systems approach in the interior point method to solve the deterministic equivalent of two-stage stochastic linear programming problem is shown to be the best solution technique. An innovation to the augmented systems approach is the augmented system factorization which promises improved computational performance by reducing computational cost as a result of factorizations. This is done using a 1 x 1 pivot scheme that provides stability.
Publication Name: European Journal of Operational Research
Subject: Business, international
ISSN: 0377-2217
Year: 1997
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