An integrated approach in production planning and scheduling
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Bibliographic Information
An integrated approach in production planning and scheduling
（Lecture notes in economics and mathematical systems, 411）
Springer-Verlag, c1994
- : gw, pbk
- : us, pbk
Available at / 51 libraries
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Hiroshima University Central Library, Interlibrary Loan
: gw : pbk509.6:D-45/HL3590003500408070
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Includes bibliographical references
Description and Table of Contents
Description
Production Management is a large field concerned with all the aspects related to production, from the very bottom decisions at the machine level, to the top-level strategic decisicns. In this book, we are concerned with production planning and scheduling aspects. Traditional production planning methodologies are based on a now widely ac cepted hierarchical decom?osition into several planning decision levels. The higher in the hierarchy, the more aggregate are the models and the more important are the decisions. In this book, we only consider the last two decision levels in the hierarchy, namely, the mid-term (or tacticaQ planning level and the short-term (or operationaQ scheduling level. In the literature and in practice, the decisions are taken in sequence and in a top-down approach from the highest level in the hierarchy to the bottom level. The decisions taken at some level in the hierarchy are constrained by those already taken at upper levels and in turn, must translate into feasible objectives for the next lower levels in the hierarchy. It is a common sense remark to say that the whole hierarchical decision process is coherent if the interactions between different levels in the hierarchy are taken into account so that a decision taken at some level in the hierarchy translates into a feasible objective for the next decision level in the hierarchy. However, and surpris ingly enough, this crucial consistency issue is rarely investigated and few results are available in the literature.
Table of Contents
I Production Planning and Scheduling.- I.1 Production Management.- I.1.1 The Production System.- I.1.2 The Management System.- I.1.3 Classification of Planning Decisions.- I.2 Production Planning.- I.3 Production Scheduling.- I.4 Planning and Scheduling.- I.4.1 Planning and Scheduling: Hierarchical Approaches.- I.4.1.1 Deterministic Approaches.- I.4.1.2 Stochastic Approaches.- I.4.2 Planning and Scheduling: Integrated Approaches.- I.4.2.1 The Economic Lot Scheduling Problem.- I.4.2.2 Simultaneous Lotsizing and Scheduling [Afentakis 85].- I.4.2.3 Interaction between Planning and Scheduling [Fontan and Imbert 85].- I.4.2.4 Integrating Scheduling with Batching and Lotsizing [Potts and Van Wassenhove 92].- I.4.3 Planning and Scheduling: Various Approaches.- I.5 Conclusion.- II Job-Shop Sequencing and Scheduling.- II.1 Introduction.- II.2 Job-Shop Scheduling.- II.2.1 Definitions.- II.2.2 Exact Methods.- II.2.3 Heuristic Procedures.- II.2.3.1 List Scheduling Algorithms.- II.2.3.2 Other Methods.- II.3 The Shifting Bottleneck Procedure.- II.3.1 Introduction.- II.3.2 The Shifting Bottleneck Procedure.- II.3.3 The One-Machine Sequencing Problem.- II.3.3.1 Introduction.- II.3.3.2 Carlier's Algorithm.- II.3.4 Remarks on the Shifting Bottleneck Procedure.- II.4 A Modified Shifting Bottleneck Procedure.- II.4.1 Drawbacks of the Shifting Bottleneck Procedure.- II.4.2 The Dependent Job Algorithm.- II.4.3 A Modified Shifting Bottleneck Procedure.- II.4.4 Computational Experiments.- II.4.4.1 The 10 x 10 and 5 x 20 Classical Examples.- II.4.4.2 Computational Results.- II.4.5 Conclusion.- II.5 A Priority Rule-Based Dispatching Heuristic.- II.6 Conclusion.- III An Integrated Planning and Scheduling Model.- III.1 Introduction.- III.2 Notation and Definitions.- III.2.1 Job-Shop Scheduling.- III.2.2 Planning.- III.3 Integrating Planning and Scheduling Decisions.- III.3.1 Introduction.- III.3.2 Multi-Period Scheduling.- III.3.3 A Linear Model in Continuous Variables.- III.3.4 Necessary Conditions.- III.3.5 Sufficient Conditions.- III.3.6 An Integrated Model with Set-Up Times.- III.4 Solving Procedures.- III.4.1 A One-Pass Procedure.- III.4.2 An Iterative Procedure.- III.4.2.1 Introduction.- III.4.2.2 The Procedure.- III.4.2.3 The Scheduling Problem.- III.4.2.4 Convergence Properties.- III.5 First Computational Results.- III.5.1 With no Set-Up Time.- III.5.2 With Set-Up Times.- III.5.3 Other Computational Results.- III.6 Conclusion.- IV Various Resolution Strategies.- IV.1 Introduction.- IV.2 Two Multi-Period Scheduling Policies.- IV.2.1 The Global Scheduling Policy.- IV.2.1.1 The Modified Shifting Bottleneck (MSB) Procedure.- IV.2.1.2 A Priority Rule-Based Dispatching (PRD) Heuristic.- IV.2.1.3 Comparison between the Two Scheduling Methods.- IV.2.2 The Period by Period Scheduling Policy.- IV.2.2.1 The Modified Shifting Bottleneck (MSB) Procedure.- IV.2.2.2 A Priority Rule-Based Dispatching (PRD) Heuristic.- IV.2.2.3 Comparison between the Two Scheduling Methods.- IV.2.3 Comparison between the Two Scheduling Policies.- IV.2.4 Other Multi-Period Scheduling Policies.- IV.3 Influence of the Backlogging Cost.- IV.4 Rolling Horizpn.- V Extensions of the Model.- V.1 Introduction.- V.2 Subcontracting.- V.2.1 Model Modifications.- V.2.2 Experimental Results.- V.3 Work-In-Process Inventories.- V.3.1 Model Modifications.- V.3.2 Experimental Results.- V.4 Lot Streaming Option.- V.4.1 Model Modifications.- V.5 Conclusion.- VI Lot Streaming.- VI.1 Introduction.- VI.2 A Lot-Streaming Procedure.- VI.2.1 Notation and Definitions.- VI.2.2 An Integrated Model.- VI.2.3 An Iterative Procedure.- VI.2.4 The Rounding Procedure.- VI.2.5 The Model with Set-Up Times.- VI.2.6 A Lower Bound.- VI.3 Computational Results.- VI.3.1 The 6 x 6 and 10 x 10 Problems.- VI.3.2 Test on a Sample.- VI.3.3 With Set-Up Times.- VI.3.4 CPU Time and Number of Iterations.- VI.4 Impact on Lotsizing Models.- VI.5 Conclusion.- Conclusion.- List of Figures.- List of Tables.
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