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Simulation of a Two-End-Product Postponement System

  • T.C. Edwin ChengEmail author
  • Jian Li
  • C.L. Johnny Wan
  • Shouyang Wang
Chapter
  • 2k Downloads
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 143)

In the last chapter, we have shown that the cost benefits of a postponement system are limited when it is implemented to a single end-product supply chain system whose customer demands are discrete and uniformly distributed. To a great extent, a lot size-reorder point system outperforms a postponement system when it is operated in its optimal or near optimal total average cost at steady state based on our results. However, it is argued that a postponement system may outperform a lot size-reorder point system if the supply chain system offers more than one end-product. This view is coherent with our findings in Chapters 2 and 3. Besides, the analysis would be more valuable if both Poisson and normal distributions are considered. In fact, it is more equitable to compare the two systems by an experimental approach instead of their long-run steady states because the steady state may be reached only after infinite periods or a very long time. In order to maintain completeness of our study, a more dynamic system is developed by simulation technique in this chapter.

Keywords

Order Quantity Customer Demand Average Inventory Total Average Cost Supply Chain System 
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.

References

  1. 66.
    Lee, H. L. and Billington, C. 1994, Designing products and processes for postponement, in Sriram, D. and Eastman, C. (editors), Management of Design: Engineering and Management Perspectives, Kluwer Academic Publishers, Boston.Google Scholar
  2. 105.
    Simchi-Levi, D., Kaminsky, P. and Simchi-Levi, E. 2000, Designing and Managing the Supply Chain, Concepts, Strategies, and Case Studies, McGraw-Hill, New York.Google Scholar
  3. 125.
    Wan, J. C. L. 2004, Postponement Strategy in Supply Chain Management (M.Phil. Thesis), Department of Logistics, The Hong Kong Polytechnic University, Hong Kong.Google Scholar
  4. 129.
    Zinn, W. 1990, Developing heuristics to estimate the impact of postponement on safety stock, The International Journal of Logistics Management, 1, 2, 11–16.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • T.C. Edwin Cheng
    • 1
    Email author
  • Jian Li
    • 2
  • C.L. Johnny Wan
    • 1
  • Shouyang Wang
    • 3
  1. 1.Department of Logistics & Maritime StudiesThe Hong Kong Polytechnic UniversityKowloonHong Kong SAR
  2. 2.School of Economics & Management Beijing University of Chemical Technology (BUCT)BeijingChina, People’s Republic
  3. 3.Chinese Academy of Sciences Academy of Mathematics & Systems ScienceBeijingChina, People’s Republic

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