Principles of inventory management: when you are down to four, order more
Material type:
TextSeries: Springer series in operations researchPublication details: New York Springer 2010 Description: xviii, 339 pISBN: 9781493938636Subject(s): Inventory control | Inventory control--Mathematical models | Mathematics | Operations research | Industrial engineering | Production managementDDC classification: 658.787015118 Summary: 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 the industry and government worlds. The prerequisite courses include introductory optimization methods, probability theory (non-measure theoretic), and stochastic processes.
| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode |
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Indian Institute of Management LRC General Stacks | Operations Management & Quantitative Techniques | 658.787015118 MUC (Browse shelf(Opens below)) | 1 | Available | 001192 |
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| 658.787 NAH Perishable inventory System | 658.787 SIL Inventory and production management in supply chains | 658.787 WAT Inventory control and management | 658.787015118 MUC Principles of inventory management: when you are down to four, order more | 658.788 RUS The handbook of logistics and distribution management: | 658.788 SUD Logistics management for international business: text and cases | 658.8 BAK Product strategy and management |
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 the industry and government worlds. The prerequisite courses include introductory optimization methods, probability theory (non-measure theoretic), and stochastic processes.
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