Advertisement

Service-Level Oriented Lot Sizing Under Stochastic Demand

  • Lars Fischer
  • Sascha Herpers
  • Michael Manitz
Conference paper
Part of the Operations Research Proceedings book series (ORP, volume 2007)

Abstract

In this paper, we analyze lot sizing under stochastic demand. The lot sizes are determined such that a target service level is met. This optimization procedure requires the calculation of the shortages and their probability distribution considering the inventory dynamics. For an example, we compare different production plans that reveal the influence of a service-level constraint on lot sizing.

Keywords

Service Level Planning Horizon Production Quantity Demand Uncertainty Stochastic Demand 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Callarman, T. E., and R. S. Hamrin (1984). A comparison of dynamic lotsizing rules for use in a single stage mrp system with demand uncertainty. International Journal of Operations and Production Management 4(2), 39–48.CrossRefGoogle Scholar
  2. 2.
    de Bodt, M. A., L. N. van Wassenhove, and L. F. Gelders (1982). Lot sizing and safety stock decisions in an mrp system with demand uncertainty. Engineering Costs and Production Economics 6(1), 67–75.CrossRefGoogle Scholar
  3. 3.
    Hadley, G., and T. M. Whitin (1963). Analysis of Inventory Systems. Englewood Cliffs: Prentice-Hall.Google Scholar
  4. 4.
    Haugen, K. K., A. Løkketangen, and D. L. Woodruff (2001). Progressive hedging as a meta-heuristic applied to stochastic lot-sizing. European Journal of Operational Research 132(1), 116–122.CrossRefGoogle Scholar
  5. 5.
    Silver, E. A. (1978). Inventory control under a probabilistic time-varying, demand pattern. AIIE Transactions 10(4), 371–379.Google Scholar
  6. 6.
    Sox, C. R. (1997). Dynamic lot sizing with random demand and nonstationary costs. Operations Research Letters 20(4), 155–164.CrossRefGoogle Scholar
  7. 7.
    Tarim, S., and B. Kingsman (2006). Modelling and computing (r n, s n) policies for inventory systems with non-stationary stochastic demand. European Journal of Operational Research 174(1), 581–599.CrossRefGoogle Scholar
  8. 8.
    Tempelmeier, H. (2006). Inventory Management in Supply Networks — Problems, Models, Solutions. Norderstedt: Books on Demand.Google Scholar
  9. 9.
    Tempelmeier, H. (2007). On the stochastic uncapacitated dynamic single-item lotsizing problem with service level constraints. European Journal of Operational Research 181(1), 184–194.CrossRefGoogle Scholar
  10. 10.
    Wemmerlöv, U., and D. Whybark (1984). Lot-sizing under uncertainty in rolling schedule environment. International Journal of Production Research 22(3), 467–484.CrossRefGoogle Scholar
  11. 11.
    Zipkin, P. H. (2000). Foundations of Inventory Management. Boston et al.: McGraw-Hill.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Lars Fischer
    • 1
  • Sascha Herpers
    • 1
  • Michael Manitz
    • 1
  1. 1.Seminar für Allgemeine Betriebswirtschaftslehre, Supply Chain Management und ProduktionUniversität zu KölnKöln

Personalised recommendations