000			02667nam a22002657a 4500
999			_c811 _d811
005			20210309115039.0
008			210309b ||||| |||| 00| 0 eng d
020			_a9781493938636
082			_a658.787015118 _bMUC
100			_aMuckstadt, John A. _92782
245			_aPrinciples of inventory management: when you are down to four, order more
260			_bSpringer _aNew York _c2010
300			_axviii, 339 p.
365			_aEURO _b59.99
490			_aSpringer series in operations research
520			_aInventories 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.
650			_aInventory control _92752
650			_aInventory control--Mathematical models _92783
650			_aMathematics _91140
650			_aOperations research _9757
650			_aIndustrial engineering _91345
650			_aProduction management _9434
700			_aSapra, Amar _92784
942			_2ddc _cBK