Management of Stochastic Demand in Make-To-Stock Manufacturing.

• Superior document: Forschungsergebnisse der Wirtschaftsuniversitaet Wien Series ; v.37
• Author: Quante, Rainer.
• Place / Publishing House: Frankfurt a.M. : : Peter Lang GmbH, Internationaler Verlag der Wissenschaften,, 2009.; Ã2010.
• Year of Publication: 2009
• Edition: 1st ed.
• Language: English
• Series: Forschungsergebnisse der Wirtschaftsuniversitaet Wien Series
• Physical Description: 1 online resource (134 pages)

Table of Contents

Cover -- List of Figures -- List of Tables -- Nomenclature -- 1 Introduction -- 1.1 Research Topic and Motivation -- 1.2 Organization, Objectives and Contributions -- 2 Demand Fulfillment in Make-to-Stock Manufacturing -- 2.1 Make-to-Stock and the Customer Order Decoupling Point -- 2.2 Structure of Advanced Planning Systems -- 2.3 Available-to-Promise -- 2.3.1 Definition -- 2.3.2 Dimensions of ATP -- 3 A Framework for Demand Management -- 3.1 Demand Management Defined -- 3.2 General Model Types for DM -- 3.2.1 Classifying Demand Management Models -- 3.2.2 Single-Class Exogenous Demand Models -- 3.2.3 Price-Based Demand Models -- 3.2.4 Quantity-Based Demand Models -- 3.3 General Software Types for DM -- 3.3.1 Classifying Demand Management Software -- 3.3.2 Single-Class Exogenous Demand Solutions -- 3.3.3 Price-Based Solutions -- 3.3.4 Quantity-Based Solutions -- 4 Demand Management Models in MTS Manufacturing -- 4.1 Matching of Model and Software Types -- 4.2 Quantity-Based DM in Manufacturing -- 4.2.1 Traditional Revenue Management -- 4.2.2 Allocated Available-to-Promise -- 4.2.3 Inventory Rationing -- 4.3 A Selected Allocation and Order Promising Model -- 4.3.1 Models Without Customer Segmentation -- 4.3.2 Models With Customer Segmentation -- 4.3.3 Search Rules for ATP Consumption -- 4.4 Summary -- 5 New Demand Management Approaches -- 5.1 A Revenue Management Approach -- 5.1.1 Model formulation -- 5.1.2 Structural properties and optimal policy -- 5.1.3 A Numerical Example -- 5.2 Approximations Based on Linear Programming -- 5.2.1 Deterministic Linear Programming -- 5.2.2 Randomized Linear Programming -- 6 Simulation Environment -- 6.1 Technical Settings and Implementation Issues -- 6.1.1 Test Environment -- 6.1.2 Implementation Issues -- 6.2 Simulation Issues -- 6.2.1 Data Generation -- 6.2.2 Simulation Options.

6.2.3 Output and Key Performance Indicators -- 7 Numerical Analysis -- 7.1 SOPA in Stochastic Environments -- 7.1.1 Base Case Analysis -- 7.1.2 Impact of Customer Classes -- 7.1.3 Impact of Customer Heterogeneity -- 7.1.4 Impact of Forecast Errors -- 7.1.5 Impact of Backlogging Costs -- 7.2 Analysis of the Revenue Management Approach -- 7.2.1 Base Case Analysis -- 7.2.2 Impact of Demand Variability -- 7.2.3 Impact of Customer Heterogeneity -- 7.2.4 Impact of Supply Shortage -- 7.3 Analysis of Randomized Linear Programming -- 7.4 Summary -- 8 Conclusion -- Appendix -- A Proofs of the Structural Properties of the RM approach -- B Data Tables.