Optimization of Stochastic Models: The Interface Between Simulation and Optimization: 373 - Rilegato
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Stochastic models are everywhere. In manufacturing, queuing models are used for modeling production processes, realistic inventory models are stochastic in nature. Stochastic models are considered in transportation and communication. Marketing models use stochastic descriptions of the demands and buyer's behaviors. In finance, market prices and exchange rates are assumed to be certain stochastic processes, and insurance claims appear at random times with random amounts. To each decision problem, a cost function is associated. Costs may be direct or indirect, like loss of time, quality deterioration, loss in production or dissatisfaction of customers. In decision making under uncertainty, the goal is to minimize the expected costs. However, in practically all realistic models, the calculation of the expected costs is impossible due to the model complexity. Simulation is the only practicable way of getting insight into such models. Thus, the problem of optimal decisions can be seen as getting simulation and optimization effectively combined. This text does not try to touch all work done in this area. Instead, many concepts are presented and treated with mathematical rigor and necessary conditions for the correctness of various approaches are stated. It is suitable as a text for a graduate level course on stochastic models or as a secondary text for a graduate level course in operations research.
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Contenuti
1. Optimization. 2. Discrete-Event Processes. 3. Derivatives. 4. Simulation and Sensitivity Estimation. 5. Stochastic Approximation. A: Metric Spaces. B: Sequences and Series. C: Matrix Algebra. D: Derivatives. E: Convexity and Convex Projections. F: Set-Wise Convergence.G: Duality and Lagrangians. H: Probability Spaces and Random Variables. I: Convergence of Random Variables. J: The Wasserstein Distance. K: Conditional Expectations. L: Martingales. M: Choquet Theory. N: Coupling. Index.
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Book by Pflug Georg Ch
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Optimization of Stochastic Models: The Interface Between Simulation and Optimization (The Springer International Series in Engineering and Computer Science (373), Band 373)
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Gebundene Ausgabe. Condizione: Wie neu. Gebraucht - Wie neu Ungelesenes, vollständiges Exemplar in sehr gutem Zustand. -Stochastic models are everywhere. In manufacturing, queuing models are used for modeling production processes, realistic inventory models are stochastic in nature. Stochastic models are considered in transportation and communication. Marketing models use stochastic descriptions of the demands and buyer's behaviors. In finance, market prices and exchange rates are assumed to be certain stochastic processes, and insurance claims appear at random times with random amounts. To each decision problem, a cost function is associated. Costs may be direct or indirect, like loss of time, quality deterioration, loss in production or dissatisfaction of customers. In decision making under uncertainty, the goal is to minimize the expected costs. However, in practically all realistic models, the calculation of the expected costs is impossible due to the model complexity. Simulation is the only practicable way of getting insight into such models. Thus, the problem of optimal decisions can be seen as getting simulation and optimization effectively combined. The field is quite new and yet the number of publications is enormous. This book does not even try to touch all work done in this area. Instead, many concepts are presented and treated with mathematical rigor and necessary conditions for the correctness of various approaches are stated. Optimization of Stochastic Models: The Interface Between Simulation and Optimization is suitable as a text for a graduate level course on Stochastic Models or as a secondary text for a graduate level course in Operations Research. 396 pp. Englisch. Codice articolo INF1000079458
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Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 400 | Sprache: Englisch | Produktart: Bücher | Stochastic models are everywhere. In manufacturing, queuing models are used for modeling production processes, realistic inventory models are stochastic in nature. Stochastic models are considered in transportation and communication. Marketing models use stochastic descriptions of the demands and buyer's behaviors. In finance, market prices and exchange rates are assumed to be certain stochastic processes, and insurance claims appear at random times with random amounts. To each decision problem, a cost function is associated. Costs may be direct or indirect, like loss of time, quality deterioration, loss in production or dissatisfaction of customers. In decision making under uncertainty, the goal is to minimize the expected costs. However, in practically all realistic models, the calculation of the expected costs is impossible due to the model complexity. Simulation is the only practicable way of getting insight into such models. Thus, the problem of optimal decisions can be seen as getting simulation and optimization effectively combined. The field is quite new and yet the number of publications is enormous. This book does not even try to touch all work done in this area. Instead, many concepts are presented and treated with mathematical rigor and necessary conditions for the correctness of various approaches are stated. Optimization of Stochastic Models: The Interface Between Simulation and Optimization is suitable as a text for a graduate level course on Stochastic Models or as a secondary text for a graduate level course in Operations Research. Codice articolo 1360756/202
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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Stochastic models are everywhere. In manufacturing, queuing models are used for modeling production processes, realistic inventory models are stochastic in nature. Stochastic models are considered in transportation and communication. Marketing models use. Codice articolo 5971720
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Stochastic models are everywhere. In manufacturing, queuing models are used for modeling production processes, realistic inventory models are stochastic in nature. Stochastic models are considered in transportation and communication. Marketing models use stochastic descriptions of the demands and buyer's behaviors. In finance, market prices and exchange rates are assumed to be certain stochastic processes, and insurance claims appear at random times with random amounts. To each decision problem, a cost function is associated. Costs may be direct or indirect, like loss of time, quality deterioration, loss in production or dissatisfaction of customers. In decision making under uncertainty, the goal is to minimize the expected costs. However, in practically all realistic models, the calculation of the expected costs is impossible due to the model complexity. Simulation is the only practicable way of getting insight into such models. Thus, the problem of optimal decisions can be seen as getting simulation and optimization effectively combined. The field is quite new and yet the number of publications is enormous. This book does not even try to touch all work done in this area. Instead, many concepts are presented and treated with mathematical rigor and necessary conditions for the correctness of various approaches are stated. Optimization of Stochastic Models: The Interface Between Simulation and Optimization is suitable as a text for a graduate level course on Stochastic Models or as a secondary text for a graduate level course in Operations Research. 400 pp. Englisch. Codice articolo 9780792397809
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Buch. Condizione: Neu. Optimization of Stochastic Models | The Interface Between Simulation and Optimization | Georg Ch. Pflug | Buch | xiv | Englisch | 1996 | Springer | EAN 9780792397809 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Codice articolo 102592892
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Condizione: New. In manufacturing, queuing models are used for modeling production processes. Realistic inventory models are stochastic in nature. Stochastic models are considered in transportation and communication. This book is suitable for a graduate level course on stochastic models or as a secondary text for a graduate level course in operations research. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 382 pages, biography. BIC Classification: KJT; PBT. Category: (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 22. Weight in Grams: 735. . 1996. Hardback. . . . . Codice articolo V9780792397809
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