Analysis of Postponement Strategy by EPQ-based Models

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

In this chapter we develop EPQ-based models with and without stockout to examine the impact of postponement. We formulate the total average cost functions of the two scenarios for producing and keeping n end-products in a supply chain, in which their demands are known and deterministic. Using standard optimization techniques , we show that postponed customization of end-products results in a lower total average cost in certain circumstances. We also find that two key factors that influence postponement decisions are variance of the machine utilization rates and variance of the backorder costs.


Supply Chain Setup Cost Customer Demand Production Quantity Total Average Cost 
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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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