Knut Haase

Lotsizing and Scheduling for Production Planning (eBook, PDF)

• Format: PDF

Produktbeschreibung

Billions of dollars are tied up in the inventories of manufacturing companies which cause large (interest) costs. A small decrease of the inventory and/or production costs without reduction of the service level can increase the profit substantially. Especially in the case of scarce capacity, efficient production schedules are fundamental for short delivery time and on-time delivery which are important competitive priorities. To support decision makers by improving their manufacturing resource planning system with appropriate methods is one of the most of production planning. interesting challenges The following chapters contain new models and new solution strategies which may be helpful for decision makers and for further research in the areas of production planning and operations research. The main subject is on lotsizing and scheduling. The objectives and further characteristics of such problems can be inferred from practical need. Thus, before an outline is given, we consider the general objectives of lotsizing and scheduling and classify the most important characteristics of such problems in the following sections.

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 118
• Erscheinungstermin: 6. Dezember 2012
• Englisch
• ISBN-13: 9783642457357
• Artikelnr.: 53130821

Inhaltsangabe

1. Introduction.- 1.1 Objectives of Lotsizing and Scheduling.- 1.2 Classification of Problems.- 1.3 Outline of the Following Chapters.- 2. Single-Level Capacitated Lotsizing Problems.- 2.1 The Capacitated Lotsizing Problem (CLSP).- 2.2 Critique on the CLSP.- 2.3 The CLSP with Linked Lotsizes (CLSPL).- 3. Single-Level Lotsizing and Scheduling Problems.- 3.1 The Discrete Lotsizing and Scheduling Problem (DLSP).- 3.2 The Continuous Setup Lotsizing Problem (CSLP).- 3.3 A New Model - The Proportional Lotsizing and Scheduling Problem (PLSP).- 3.4 Model Comparison.- 4. Extensions of the PLSP.- 4.1 The PLSP with Setup Times.- 4.2 The PLSP with Sequence Dependent Setup Costs.- 4.3 The Multi-Machine PLSP with Make-or-Buy Decisions.- 4.4 The PLSP with Backordering and Stockouts.- 4.5 The Multi-Level PLSP with One Bottleneck.- 4.6 Concluding Remarks.- 5. Control of Stochastic Algorithms via Sequential Analysis.- 5.1 Hypotheses Test Problem for Reducing the Parameter Space.- 5.2 Sequential Tests of Hypotheses Concerning Quantiles.- 5.3 Monte-Carlo Study for Sequential Tests.- 5.4 An Example.- 5.5 Concluding Remarks.- 6. A New Class of Stochastic Heuristics for the PLSP and the CLSPL.- 6.1 Biased Random Sampling via Randomized Regrets for the PLSP.- 6.2 Regrets for PLSP Extensions.- 6.3 Modifications for the CLSPL.- 6.4 Integration of Parameter Control via Sequential Analysis.- 6.5 Relations to Local Search Methods.- 7. Computational Results.- 7.1 An Instance Generator.- 7.2 Computational Results for the PLSP.- 7.3 Computational Results for the CLSPL.- 8. Summary and Future Work.- Appendix Monte-Carlo Study for Sequential Tests.