Dynamic lot sizing problems with stochastic production output (PDF)
(Sprache: Englisch)
In the real world, production systems are affected by external and internal uncertainties. Stochastic demand - an external uncertainty - arises mainly due to forecast errors and unknown behavior of customers in future. Internal uncertainties occur in...
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In the real world, production systems are affected by external and internal uncertainties. Stochastic demand - an external uncertainty - arises mainly due to forecast errors and unknown behavior of customers in future. Internal uncertainties occur in situations where random yield, random production capacity, or stochastic processing times affect the productivity of a manufacturing system. The resulting stochastic production output is especially present in industries with modern and complex technologies as the semiconductor industry.
This thesis provides model formulations and solution methods for capacitated dynamic lot sizing problems with stochastic demand and stochastic production output that can be used by practitioners within Manufacturing Resource Planning Systems (MRP), Capacitated Production Planning Systems (CPPS), and Advanced Planning Systems (APS). In all models, backordered demand is controlled with service levels. Numerical studies compare the solution methods and give managerial implications in presence of stochastic production output.
This book addresses practitioners, consultants, and developers as well as students, lecturers, and researchers with focus on lot sizing, production planning, and supply chain management.
This thesis provides model formulations and solution methods for capacitated dynamic lot sizing problems with stochastic demand and stochastic production output that can be used by practitioners within Manufacturing Resource Planning Systems (MRP), Capacitated Production Planning Systems (CPPS), and Advanced Planning Systems (APS). In all models, backordered demand is controlled with service levels. Numerical studies compare the solution methods and give managerial implications in presence of stochastic production output.
This book addresses practitioners, consultants, and developers as well as students, lecturers, and researchers with focus on lot sizing, production planning, and supply chain management.
Autoren-Porträt von Michael Kirste
Michael Kirste is a research associate at the Department of Supply Chain Management and Production at the University of Cologne, Germany.
Bibliographische Angaben
- Autor: Michael Kirste
- 2017, 1. Auflage, 248 Seiten, Englisch
- Verlag: Books on Demand
- ISBN-10: 3744845508
- ISBN-13: 9783744845502
- Erscheinungsdatum: 30.06.2017
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Größe: 2.36 MB
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Englisch
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