Woodruff / Voß | Introduction to Computational Optimization Models for Production Planning in a Supply Chain | Buch | 978-3-642-06755-6 | sack.de

Buch, Englisch, 260 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 417 g

Woodruff / Voß

Introduction to Computational Optimization Models for Production Planning in a Supply Chain

Buch, Englisch, 260 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 417 g

ISBN: 978-3-642-06755-6
Verlag: Springer


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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Zielgruppe


Research

Weitere Infos & Material


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.


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