Stochastic optimization on Bayesian nets

Stochastic optimization on Bayesian nets

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Article ID: iaor19992037
Country: Netherlands
Volume: 101
Issue: 2
Start Page Number: 360
End Page Number: 373
Publication Date: Sep 1997
Journal: European Journal of Operational Research
Authors: , ,
Abstract:

In this paper we are concerned with stochastic optimization problems in the case when the joint probability distribution, associated with random parameters, can be described by means of a Bayesian net. In such a case we suggest that the structured nature of the probability distribution can be exploited for designing efficient gradient estimation algorithm. Such gradient estimates can be used within the general framework of stochastic gradient (quasi-gradient) solution procedures in order to solve complex non-linear stochastic optimization problems. We describe a gradient estimation algorithm and present a case study related to reliability of semiconductor manufacturing together with numerical experiments.

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