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  • 1
    Online-Ressource
    Online-Ressource
    Frankfurt a.M. :Peter Lang GmbH, Internationaler Verlag der Wissenschaften,
    UID:
    almahu_9949568774602882
    Umfang: 1 online resource (134 pages)
    Ausgabe: 1st ed.
    ISBN: 9783631753866
    Serie: Forschungsergebnisse der Wirtschaftsuniversitaet Wien Series ; v.37
    Anmerkung: 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.
    Weitere Ausg.: Print version: Quante, Rainer Management of Stochastic Demand in Make-To-Stock Manufacturing Frankfurt a.M. : Peter Lang GmbH, Internationaler Verlag der Wissenschaften,c2009 ISBN 9783631594094
    Sprache: Englisch
    Schlagwort(e): Electronic books. ; Hochschulschrift
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 2
    Online-Ressource
    Online-Ressource
    Frankfurt a.M. : Peter Lang GmbH, Internationaler Verlag der Wissenschaften
    UID:
    almahu_9948168434002882
    Umfang: 1 online resource
    Ausgabe: 1st, New ed.
    ISBN: 9783631753866
    Serie: Forschungsergebnisse der Wirtschaftsuniversität Wien 37
    Inhalt: Up to now, demand fulfillment in make-to-stock manufacturing is usually handled by advanced planning systems. Orders are fulfilled on the basis of simple rules or deterministic planning approaches not taking into account demand fluctuations. The consideration of different customer classes as it is often done today requires more sophisticated approaches explicitly considering stochastic influences. This book reviews current literature, presents a framework that addresses revenue management and demand fulfillment at once and introduces new stochastic approaches for demand fulfillment in make-to-stock manufacturing based on the ideas of the revenue management literature.
    Anmerkung: Doctoral Thesis , Contents: Demand Fulfillment in Make-to-Stock Manifacturing – A Framework for Demand Management – Demand Management Models in Make-to-Stock Manifacturing – Advanced Planning Systems – Available-to-Promise – Allocation and Order Promising – Revenue Management – Randomized Linear Programming.
    Weitere Ausg.: ISBN 9783631594094
    Sprache: Englisch
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 3
    Online-Ressource
    Online-Ressource
    Frankfurt am Main ; : Lang,
    UID:
    kobvindex_HPB1082878837
    Umfang: 1 online resource
    ISBN: 9783631594094 , 3631594097 , 9783631753866 , 3631753861
    Serie: Forschungsergebnisse der Wirtschaftsuniversitaet Wien Series ; v.37
    Inhalt: Up to now, demand fulfillment in make-to-stock manufacturing is usually handled by advanced planning systems. Orders are fulfilled on the basis of simple rules or deterministic planning approaches not taking into account demand fluctuations. The consideration of different customer classes as it is often done today requires more sophisticated approaches explicitly considering stochastic influences. This book reviews current literature, presents a framework that addresses revenue management and demand fulfillment at once and introduces new stochastic approaches for demand fulfillment in make-to-stock manufacturing based on the ideas of the revenue management literature.
    Anmerkung: 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. , English.
    Weitere Ausg.: Print version: Quante, Rainer Management of Stochastic Demand in Make-To-Stock Manufacturing Frankfurt a.M. : Peter Lang GmbH, Internationaler Verlag der Wissenschaften,c2009 ISBN 9783631594094
    Sprache: Englisch
    Schlagwort(e): Electronic books.
    URL: JSTOR
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 4
    Buch
    Buch
    Frankfurt am Main [u.a.] : Peter Lang GmbH
    UID:
    kobvindex_ZLB15115863
    Umfang: 128 Seiten , graph. Darst.
    ISBN: 9783631594094
    Serie: Forschungsergebnisse der WU Wirtschaftsuniversität Wien 37
    Anmerkung: Text engl.
    Sprache: Englisch
    Schlagwort(e): Serienfertigung
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 5
    Online-Ressource
    Online-Ressource
    Frankfurt am Main :Peter Lang GmbH, Internationaler Verlag der Wissenschaften,
    UID:
    edoccha_9958982574702883
    Umfang: 1 online resource (128 pages)
    Ausgabe: First edition
    ISBN: 3-631-75386-1
    Serie: Forschungsergebnisse der Wirtschaftsuniversitaet Wien.
    Inhalt: Up to now, demand fulfillment in make-to-stock manufacturing is usually handled by advanced planning systems. Orders are fulfilled on the basis of simple rules or deterministic planning approaches not taking into account demand fluctuations. The consideration of different customer classes as it is often done today requires more sophisticated approaches explicitly considering stochastic influences. This book reviews current literature, presents a framework that addresses revenue management and demand fulfillment at once and introduces new stochastic approaches for demand fulfillment in make-to-stock manufacturing based on the ideas of the revenue management literature.
    Anmerkung: 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. , English.
    Weitere Ausg.: ISBN 3-631-59409-7
    Sprache: Englisch
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 6
    Online-Ressource
    Online-Ressource
    Frankfurt am Main :Peter Lang GmbH, Internationaler Verlag der Wissenschaften,
    UID:
    almahu_9949561338502882
    Umfang: 1 online resource (128 pages)
    Ausgabe: First edition
    ISBN: 3-631-75386-1
    Serie: Forschungsergebnisse der Wirtschaftsuniversitaet Wien.
    Inhalt: Up to now, demand fulfillment in make-to-stock manufacturing is usually handled by advanced planning systems. Orders are fulfilled on the basis of simple rules or deterministic planning approaches not taking into account demand fluctuations. The consideration of different customer classes as it is often done today requires more sophisticated approaches explicitly considering stochastic influences. This book reviews current literature, presents a framework that addresses revenue management and demand fulfillment at once and introduces new stochastic approaches for demand fulfillment in make-to-stock manufacturing based on the ideas of the revenue management literature.
    Anmerkung: 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. , English.
    Weitere Ausg.: ISBN 3-631-59409-7
    Sprache: Englisch
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 7
    Online-Ressource
    Online-Ressource
    Frankfurt am Main :Peter Lang GmbH, Internationaler Verlag der Wissenschaften,
    UID:
    edocfu_9958982574702883
    Umfang: 1 online resource (128 pages)
    Ausgabe: First edition
    ISBN: 3-631-75386-1
    Serie: Forschungsergebnisse der Wirtschaftsuniversitaet Wien.
    Inhalt: Up to now, demand fulfillment in make-to-stock manufacturing is usually handled by advanced planning systems. Orders are fulfilled on the basis of simple rules or deterministic planning approaches not taking into account demand fluctuations. The consideration of different customer classes as it is often done today requires more sophisticated approaches explicitly considering stochastic influences. This book reviews current literature, presents a framework that addresses revenue management and demand fulfillment at once and introduces new stochastic approaches for demand fulfillment in make-to-stock manufacturing based on the ideas of the revenue management literature.
    Anmerkung: 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. , English.
    Weitere Ausg.: ISBN 3-631-59409-7
    Sprache: Englisch
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
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