Finding the best in the presence of a stochastic constraint

Finding the best in the presence of a stochastic constraint

Our problem is that of finding the best system - i.e., the system with the largest or smallest primary performance measure - among a finite number of simulated systems in the presence of a stochastic constraint on a secondary performance measure. In order to solve this problem, we first find a set t...

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Hauptverfasser: Andradottir, S., Goldsman, D., Seong-Hee Kim
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Sprache:eng
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Constraint optimization
Environmental economics
Modeling
Random variables
Sampling methods
Stochastic processes
Stochastic systems
Systems engineering and theory
Utility theory
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creator Andradottir, S.
Goldsman, D.
Seong-Hee Kim
description Our problem is that of finding the best system - i.e., the system with the largest or smallest primary performance measure - among a finite number of simulated systems in the presence of a stochastic constraint on a secondary performance measure. In order to solve this problem, we first find a set that contains only feasible or near-feasible systems (phase I) and then choose the best among those systems in the set (phase II). We present a statistically valid procedure for phase I and then propose another procedure that performs phases I and II sequentially to find the best feasible system. Finally, we provide some experimental results for the second procedure.
doi_str_mv 10.1109/WSC.2005.1574315
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subjects Constraint optimization
Environmental economics
Modeling
Random variables
Sampling methods
Stochastic processes
Stochastic systems
Systems engineering and theory
Utility theory
title Finding the best in the presence of a stochastic constraint
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