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Introduction to Computational Optimization Models for Production Planning in a Supply Chain [electronic resource] / by Stefan Voß, David L. Woodruff.

By: Contributor(s): Material type: TextTextPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2006Edition: 2nd ed. 2006Description: XII, 260 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540298793
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 330.015195
LOC classification:
  • HB139-141
Online resources:
Contents:
Optimization Modeling -- Starting with an mrp Model -- Extending to an MRP II Model -- A Better Model -- Extensions to the Model -- Implementation Examples -- Solutions -- Some Stochastic Extensions -- Research Directions and References.
In: Springer Nature eBookSummary: provide models that could be used by do-it-yourselfers and also can be used toprovideunderstandingofthebackgroundissuessothatonecandoabetter job of working with the (proprietary) algorithms of the software vendors. In this book we strive to provide models that capture many of the - tails faced by ?rms operating in a modern supply chain, but we stop short of proposing models for economic analysis of the entire multi-player chain. In other words, we produce models that are useful for planning within a supply chain rather than models for planning the supply chain. The usefulness of the models is enhanced greatly by the fact that they have been implemented - ing computer modeling languages. Implementations are shown in Chapter 7, which allows solutions to be found using a computer. A reasonable question is: why write the book now? It is a combination of opportunities that have recently become available. The availability of mod- inglanguagesandcomputersthatprovidestheopportunitytomakepractical use of the models that we develop. Meanwhile, software companies are p- viding software for optimized production planning in a supply chain. The opportunity to make use of such software gives rise to a need to understand some of the issues in computational models for optimized planning. This is best done by considering simple models and examples.
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Optimization Modeling -- Starting with an mrp Model -- Extending to an MRP II Model -- A Better Model -- Extensions to the Model -- Implementation Examples -- Solutions -- Some Stochastic Extensions -- Research Directions and References.

provide models that could be used by do-it-yourselfers and also can be used toprovideunderstandingofthebackgroundissuessothatonecandoabetter job of working with the (proprietary) algorithms of the software vendors. In this book we strive to provide models that capture many of the - tails faced by ?rms operating in a modern supply chain, but we stop short of proposing models for economic analysis of the entire multi-player chain. In other words, we produce models that are useful for planning within a supply chain rather than models for planning the supply chain. The usefulness of the models is enhanced greatly by the fact that they have been implemented - ing computer modeling languages. Implementations are shown in Chapter 7, which allows solutions to be found using a computer. A reasonable question is: why write the book now? It is a combination of opportunities that have recently become available. The availability of mod- inglanguagesandcomputersthatprovidestheopportunitytomakepractical use of the models that we develop. Meanwhile, software companies are p- viding software for optimized production planning in a supply chain. The opportunity to make use of such software gives rise to a need to understand some of the issues in computational models for optimized planning. This is best done by considering simple models and examples.

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