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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
This is a proceedings volume of a workshop on"Computationally intensive methods in Simulation andOptimization". The purpose of the meeting was to review andevaluate newly developed methods for combining simulationandoptimization. These methods are used for decisionproblems about stochastic systems like production systems orcommunication networks, which are too complex for beingmodeled in an analytic way. A simulation model for such asystem is the basis for an efficient use of recursivestochastic optimization techniques.The volume contains selected papers from three areas:1. Gradient techniques for discrete event simulation models2. Stochastic optimization methods3. Efficient random generation methodsThe book contains articles dealing with competing methodslike the score method, perturbation analysis andexperimental design techniques. For the first time, acomparision between these techniques is made.
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
This is a proceedings volume of a workshop on"Computationally intensive methods in Simulation andOptimization". The purpose of the meeting was to review andevaluate newly developed methods for combining simulationandoptimization. These methods are used for decisionproblems about stochastic systems like production systems orcommunication networks, which are too complex for beingmodeled in an analytic way. A simulation model for such asystem is the basis for an efficient use of recursivestochastic optimization techniques.The volume contains selected papers from three areas:1. Gradient techniques for discrete event simulation models2. Stochastic optimization methods3. Efficient random generation methodsThe book contains articles dealing with competing methodslike the score method, perturbation analysis andexperimental design techniques. For the first time, acomparision between these techniques is made.