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Optimization for simulation: LAD accelerator
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DOI：10.1007/s10479-009-0518-3.png)
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Abstract
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The goal of this paper is to address the problem of evaluating the performance of a system running under unknown values for its stochastic parameters. A new approach called LAD for Simulation, based on simulation and classification software, is presented. It uses a number of simulations with very few replications and records the mean value of directly measurable quantities (called observables). These observables are used as input to a classification model that produces a prediction for the performance of the system. Application to an assemble-to-order system from the literature is described and detailed results illustrate the strength of the method.
Keywords:
Simulation-optimization
Logical analysis of data
Stochastic models
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