Stochastic models

One of the central problems in operations research and management science is how to quantify the effects of uncertainty about the future. This, the second volume in a series of handbooks, is devoted to models where chance events play a major role. The thirteen chapters survey topics in applied proba...

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Detalles Bibliográficos
Otros Autores: Heyman, Daniel P. (-), Sobel, Matthew J.
Formato: Libro electrónico
Idioma:Inglés
Publicado: Amsterdam ; New York : North-Holland 1990.
Colección:Science Direct e-books.
Handbooks in operations research and management science ; 2.
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b34745233*spi
Descripción
Sumario:One of the central problems in operations research and management science is how to quantify the effects of uncertainty about the future. This, the second volume in a series of handbooks, is devoted to models where chance events play a major role. The thirteen chapters survey topics in applied probability that have been particularly useful in operations research and management science. Each chapter was written by an expert, both in subject matter and in its exposition. The chapters fall into four groups. The first four cover the fundamentals of stochastic processes, and lay the foundation for the following chapters. The next three chapters are concerned with methods of getting numbers. This includes numerical solution of models, parameter estimation for models, and simulation of models. Chapters 8 and 9 describe the fundamentals of dynamic optimization. The last four chapters are concerned with the most important structured models in operations research and management science; queues, queueing networks, inventories, and reliability.
Descripción Física:1 recurso electrónico (xv, 723 p.)
Formato:Forma de acceso: World Wide Web.
Bibliografía:Incluye referencias bibliográficas e índice.
ISBN:9780444874733
9780444599247
9780444887054