Optimization for Simulation: LAD Accelerator
Miguel Lejeune (mlejeunegwu.edu)
Abstract: 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
Category 1: Other Topics (Optimization of Simulated Systems )
Category 2: Global Optimization (Stochastic Approaches )
Category 3: Applications -- Science and Engineering (Data-Mining )
Citation: Accepted for publication in Annals of Operations Research.
Entry Submitted: 07/03/2007
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