Sample-path optimization of convex stochastic performance functions

Sample-path optimization of convex stochastic performance functions

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Article ID: iaor1998385
Country: Netherlands
Volume: 75
Issue: 2
Start Page Number: 137
End Page Number: 176
Publication Date: Nov 1996
Journal: Mathematical Programming
Authors: , , ,
Keywords: programming: convex
Abstract:

In this paper we propose a method for optimizing convex performance functions in stochastic systems. These functions can include expected performance in static systems and steady-state performance in discrete-event dynamic systems; they may be nonsmooth. The method is closely related to retrospective simulation optimization; it appears to overcome some limitations of stochastic approximation, which is often applied to such problems. We explain the method and give computational results for two classes of problems: tandem production lines with up to 50 machines, and stochastic PERT (Program Evaluation and Review Technique) problems with up to 70 nodes and 110 arcs.

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