A Sample-Based Method for Perishable Good Inventory Control with a Service Level Constraint

  • Eligius M. T. Hendrix
  • Karin G. J. Pauls-Worm
  • Roberto Rossi
  • Alejandro G. Alcoba
  • Rene Haijema
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9335)

Abstract

This paper studies the computation of so-called order-up-to levels for a stochastic programming inventory problem of a perishable product. Finding a solution is a challenge as the problem enhances a perishable product, fixed ordering cost and non-stationary stochastic demand with a service level constraint. An earlier study [7] derived order-up-to values via an MILP approximation. We consider a computational method based on the so-called Smoothed Monte Carlo method using sampled demand to optimize values. The resulting MINLP approach uses enumeration, bounding and iterative nonlinear optimization.

Keywords

Inventory control Perishable products MINLP Chance constraint Monte Carlo 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Eligius M. T. Hendrix
    • 1
  • Karin G. J. Pauls-Worm
    • 2
  • Roberto Rossi
    • 3
  • Alejandro G. Alcoba
    • 1
  • Rene Haijema
    • 2
  1. 1.Computer ArchitectureUniversidad de MálagaMálagaSpain
  2. 2.Operations Research and LogisticsWageningen UniversityWageningenNetherlands
  3. 3.Business SchoolEdinburgh UniversityEdinburghUK

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