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04307nam a22006015i 4500 |
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978-0-387-27288-7 |
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100301s2005 xxu| s |||| 0|eng d |
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|a 9780387272887
|9 978-0-387-27288-7
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|a 10.1007/b138879
|2 doi
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|a BUS049000
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|a 658.40301
|2 23
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|a Muckstadt, John A.
|e author.
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|a Analysis and Algorithms for Service Parts Supply Chains
|h [electronic resource] /
|c by John A. Muckstadt.
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|a New York, NY :
|b Springer New York,
|c 2005.
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300 |
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|a XVIII, 278 p. 57 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a Springer Series in Operations Research and Financial Engineering,
|x 1431-8598
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|a Background: Analysis of (s-1, s) and Order-Up-To Policies -- Background Concepts: An Introduction to the (s-1, s) Policy under Poisson and Compound Poisson Demand -- An Exact Model for a Depot-Base Two Echelon Inventory and Repair System -- Tactical Planning Models for Managing Recoverable Items -- A Continuous Time, Multi-Echelon, Multi-Item System with Time-Based Service Level Constraints -- Lateral Resupply and Pooling in Multi-Echelon Systems -- Capacity-limited Systems -- Extension of Palm’s Theorem to Nonstationary Demand Processes -- Real-time Execution Systems.
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|a Services requiring parts has become a $1.5 trillion business annually worldwide, creating a tremendous incentive to manage the logistics of these parts efficiently by making planning and operational decisions in a rational and rigorous manner. This book provides a broad overview of modeling approaches and solution methodologies for addressing service parts inventory problems found in high-powered technology and aerospace applications. The focus in this work is on the management of high cost, low demand rate service parts found in multi-echelon settings. This unique book, with its breadth of topics and mathematical treatment, begins by first demonstrating the optimality of an order-up-to policy [or (s-1,s)] in certain environments. This policy is used in the real world and studied throughout the text. The fundamental mathematical building blocks for modeling and solving applications of stochastic process and optimization techniques to service parts management problems are summarized extensively. A wide range of exact and approximate mathematical models of multi-echelon systems is developed and used in practice to estimate future inventory investment and part repair requirements. The text may be used in a variety of courses for first-year graduate students or senior undergraduates, as well as for practitioners, requiring only a background in stochastic processes and optimization. It will serve as an excellent reference for key mathematical concepts and a guide to modeling a variety of multi-echelon service parts planning and operational problems.
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|a Business.
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|a Operations research.
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|a Decision making.
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|a Applied mathematics.
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|a Engineering mathematics.
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|a Mathematical models.
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|a Calculus of variations.
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|a Probabilities.
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|a Engineering economics.
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|a Engineering economy.
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|a Business and Management.
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|a Operation Research/Decision Theory.
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650 |
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|a Probability Theory and Stochastic Processes.
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650 |
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|a Applications of Mathematics.
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|a Mathematical Modeling and Industrial Mathematics.
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650 |
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|a Calculus of Variations and Optimal Control; Optimization.
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|a Engineering Economics, Organization, Logistics, Marketing.
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710 |
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9780387227153
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830 |
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|a Springer Series in Operations Research and Financial Engineering,
|x 1431-8598
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856 |
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|u http://dx.doi.org/10.1007/b138879
|z Full Text via HEAL-Link
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912 |
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|a ZDB-2-SMA
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950 |
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|a Mathematics and Statistics (Springer-11649)
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