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Lotsizing and Scheduling for Production Planning

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, efficie...

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Bibliographic Details
Main Author: Haase, Knut
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 1994, 1994
Edition:1st ed. 1994
Series:Lecture Notes in Economics and Mathematical Systems
Subjects:
Operations Management
Operations Research
Industrial Engineering
Production Management
Operations Research/decision Theory
Decision Making
Industrial And Production Engineering
Production Engineering
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
Table of Contents:
  • 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

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