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Principles of Inventory Management When You Are Down to Four, Order More /
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 us...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York, NY :
Springer New York : Imprint: Springer,
2010.
|
| Edición: | 1st ed. 2010. |
| Colección: | Springer Series in Operations Research and Financial Engineering,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 100 | 1 | |a Muckstadt, John A. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Principles of Inventory Management |h [electronic resource] : |b When You Are Down to Four, Order More / |c by John A. Muckstadt, Amar Sapra. |
| 250 | |a 1st ed. 2010. | ||
| 264 | 1 | |a New York, NY : |b Springer New York : |b Imprint: Springer, |c 2010. | |
| 300 | |a XVIII, 339 p. |b online resource. | ||
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| 490 | 1 | |a Springer Series in Operations Research and Financial Engineering, |x 2197-1773 | |
| 505 | 0 | |a Inventories Are Everywhere -- EOQ Model -- Power-of-Two Policies -- Dynamic Lot Sizing with Deterministic Demand -- Single-Period Models -- Inventory Planning over Multiple Time Periods: Linear-Cost Case -- Background Concepts: An Introduction to the ( #x2212; 1, ) Policy under Poisson Demand -- A Tactical Planning Model for Managing Recoverable Items in Multi-Echelon Systems -- Reorder Point, Lot Size Models: The Continuous Review Case -- Lot Sizing Models: The Periodic Review Case. | |
| 520 | |a 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. | ||
| 650 | 0 | |a Production management. | |
| 650 | 0 | |a Operations research. | |
| 650 | 0 | |a Management science. | |
| 650 | 0 | |a Mathematics. | |
| 650 | 0 | |a Industrial engineering. | |
| 650 | 0 | |a Production engineering. | |
| 650 | 1 | 4 | |a Operations Management. |
| 650 | 2 | 4 | |a Operations Research, Management Science . |
| 650 | 2 | 4 | |a Operations Research and Decision Theory. |
| 650 | 2 | 4 | |a Applications of Mathematics. |
| 650 | 2 | 4 | |a Industrial and Production Engineering. |
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