This textbook presents models and solutions in inventory management. It begins with a "must-read" chapter discussing basic terminology, concepts, taxonomy, and tenets of inventory system and common mathematical assumptions underlying the models. With a systematic organization, it then presents various models such as the EOQ model, lot-sizing models, Newsvendor model, periodic review models with variable and fixed ordering cost, and a continuous time model. Additionally, it discusses methods in multiechelon systems. In summary it tries to establish relationships between the dicussed models and real situations and discusses some examples in detail. Not directly competitive with other textbooks in this field, (more mathematical than some, less than others) this graduate textbook will appeal to senior and first year graduate students in operations research, industrial engineering, and quantitative MBA programs and can also serve as a reference to persons in the industry.
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Inventories are prevalent everywhere in the commercial world, whether it be in retail stores, manufacturing facilities, government stockpile material, Federal Reserve banks, or even your own household. This textbook examines basic mathematical techniques used to sufficiently manage inventories by using various computational methods and mathematical models. Such models discussed include: EOQ model and extensions, power-of-two models, single and multi-period models, probabilistic lot sizing models, multi-echelon stochastic models, Laplace and Normal demand models, exact Poisson model, and many more.
Principles of Inventory Management begins with an introductory chapter in which the basics of inventory systems and mathematical assumptions for all models are grouped together. The text is presented in a way such that each section can be read independently, and so the order in which the reader approaches the book can be inconsequential. It contains both deterministic and stochastic models along with algorithms that can be employed to find solutions to a variety of inventory control problems.
Key topics include:
* Economic order quantity (EOQ) model
* Power-of-two policies
* Dynamic lot sizing
* Single and multi-period stochastic models
* Echelon-based approaches
* Multi-echelon systems
* Single and multi-item models
With exercises at the end of each chapter and a clear, systematic exposition, this textbook will appeal to advanced undergraduate and first-year graduate students in operations research, industrial engineering, and quantitative MBA programs. It also serves as a reference for professionals in both industry and government worlds. The prerequisite courses include introductory optimization methods, probability theory (non-measure theoretic), and stochastic processes.
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Taschenbuch. Zustand: Neu. Neuware -Inventories are prevalent everywhere in the commercial world, whether it be in retail stores, manufacturing facilities, government stockpile material, Federal Reserve banks, or even your own household. This textbook examines basic mathematical techniques used to sufficiently manage inventories by using various computational methods and mathematical models. Such models discussed include: EOQ model and extensions, power-of-two models, single and multi-period models, probabilistic lot sizing models, multi-echelon stochastic models, Laplace and Normal demand models, exact Poisson model, and many more.Principles of Inventory Management begins with an introductory chapter in which the basics of inventory systems and mathematical assumptions for all models are grouped together. The text is presented in a way such that each section can be read independently, and so the order in which the reader approaches the book can be inconsequential. It contains both deterministic and stochastic models along with algorithms that can be employed to find solutions to a variety of inventory control problems.Key topics include:\* Economic order quantity (EOQ) model\* Power-of-two policies\* Dynamic lot sizing\* Single and multi-period stochastic models\* Echelon-based approaches\* Multi-echelon systems\* Single and multi-item models.With exercises at the end of each chapter and a clear, systematic exposition, this textbook will appeal to advanced undergraduate and first-year graduate students in operations research, industrial engineering, and quantitative MBA programs. It also serves as a reference for professionals in both industry and government worlds. The prerequisite courses include introductory optimization methods, probability theory (non-measure theoretic), and stochastic processes.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 360 pp. Englisch. Artikel-Nr. 9781493938636
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Inventories are prevalent everywhere in the commercial world, whether it be in retail stores, manufacturing facilities, government stockpile material, Federal Reserve banks, or even your own household. This textbook examines basic mathematical techniques used to sufficiently manage inventories by using various computational methods and mathematical models. Such models discussed include: EOQ model and extensions, power-of-two models, single and multi-period models, probabilistic lot sizing models, multi-echelon stochastic models, Laplace and Normal demand models, exact Poisson model, and many more.Principles of Inventory Management begins with an introductory chapter in which the basics of inventory systems and mathematical assumptions for all models are grouped together. The text is presented in a way such that each section can be read independently, and so the order in which the reader approaches the book can be inconsequential. It contains both deterministic and stochastic models along with algorithms that can be employed to find solutions to a variety of inventory control problems.Key topics include:\* Economic order quantity (EOQ) model\* Power-of-two policies\* Dynamic lot sizing\* Single and multi-period stochastic models \* Echelon-based approaches\* Multi-echelon systems\* Single and multi-item models.With exercises at the end of each chapter and a clear, systematic exposition, this textbook will appeal to advanced undergraduate and first-year graduate students in operations research, industrial engineering, and quantitative MBA programs. It also serves as a reference for professionals in both industry and government worlds. The prerequisite courses include introductory optimization methods, probability theory (non-measure theoretic), and stochastic processes. Artikel-Nr. 9781493938636
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