Blood platelet inventory management

R. Haijema, N.M. van Dijk, J. van der Wal

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

2 Citations (Scopus)

Abstract

This paper illustrates how MDP or Stochastic Dynamic Programming (SDP) can be used in practice for blood management at blood banks; both to set regular production quantities for perishable blood products (platelets) and how to do so in irregular periods (as holidays). The state space is too large to solve most practical problems using SDP. Nevertheless an SDP approach is still argued and shown to be most useful in combination with simulation. First the recipe for the stationary case is briefly reviewed as referred to earlier research. Here the regular production problem is periodic: demand and supply are weekday dependent but across weeks the problem is usually regarded as stationary. However, during a number of periods per year (roughly monthly) the problem is complicated by holiday periods and other events that imply non-stationary demand and production processes. This chapter particularly focuses on how to deal with the Blood Platelet (PPP) problem in non-stationary periods caused by holidays. How should production quantities anticipate holidays and how should production resume after holidays. The problem will therefore also be modelled as a finite horizon problem. To value products left in stock at the end of the horizon we propose to use the relative state values of the original periodic SDP. An optimal policy is derived by SDP. The structure of optimal policies is investigated by simulation. Next to its stationary results, as reported before, the combination of SDP and simulation so becomes of even more practical value to blood bank managers. Results show how outdating or product waste of blood platelets can be reduced from over 15% to 1% or even less, while maintaining shortage at a very low level.
Original languageEnglish
Title of host publicationMarkov Decision Processes in Practice
EditorsRichard J. Boucherie, Nico M. van Dijk
Place of PublicationCham
PublisherSpringer
Pages293-317
Number of pages25
ISBN (Electronic)978-3-319-47766-4
ISBN (Print)978-3-319-47764-0
DOIs
Publication statusPublished - 2017

Publication series

NameInternational Series in Operations Research
PublisherSpringer International Publishing
Volume248
ISSN (Print)0884-8289
ISSN (Electronic)2214-7934

Fingerprint

Inventory management
Stochastic dynamic programming
Holidays
Optimal policy
Simulation
Demand and supply
Non-stationary demand
Managers
Product value
Résumé
State space
Dynamic simulation
Shortage
Finite horizon
Production process

Keywords

  • Non-stationary
  • Finite horizon
  • Perishable products
  • Blood platelets
  • Blood inventory management

Cite this

Haijema, R., van Dijk, N. M., & van der Wal, J. (2017). Blood platelet inventory management. In R. J. Boucherie, & N. M. van Dijk (Eds.), Markov Decision Processes in Practice (pp. 293-317). (International Series in Operations Research; Vol. 248). Cham: Springer. https://doi.org/10.1007/978-3-319-47766-4_10
Haijema, R. ; van Dijk, N.M. ; van der Wal, J. / Blood platelet inventory management. Markov Decision Processes in Practice. editor / Richard J. Boucherie ; Nico M. van Dijk. Cham : Springer, 2017. pp. 293-317 (International Series in Operations Research).
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Haijema, R, van Dijk, NM & van der Wal, J 2017, Blood platelet inventory management. in RJ Boucherie & NM van Dijk (eds), Markov Decision Processes in Practice. International Series in Operations Research, vol. 248, Springer, Cham, pp. 293-317. https://doi.org/10.1007/978-3-319-47766-4_10

Blood platelet inventory management. / Haijema, R.; van Dijk, N.M.; van der Wal, J.

Markov Decision Processes in Practice. ed. / Richard J. Boucherie; Nico M. van Dijk. Cham : Springer, 2017. p. 293-317 (International Series in Operations Research; Vol. 248).

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

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AB - This paper illustrates how MDP or Stochastic Dynamic Programming (SDP) can be used in practice for blood management at blood banks; both to set regular production quantities for perishable blood products (platelets) and how to do so in irregular periods (as holidays). The state space is too large to solve most practical problems using SDP. Nevertheless an SDP approach is still argued and shown to be most useful in combination with simulation. First the recipe for the stationary case is briefly reviewed as referred to earlier research. Here the regular production problem is periodic: demand and supply are weekday dependent but across weeks the problem is usually regarded as stationary. However, during a number of periods per year (roughly monthly) the problem is complicated by holiday periods and other events that imply non-stationary demand and production processes. This chapter particularly focuses on how to deal with the Blood Platelet (PPP) problem in non-stationary periods caused by holidays. How should production quantities anticipate holidays and how should production resume after holidays. The problem will therefore also be modelled as a finite horizon problem. To value products left in stock at the end of the horizon we propose to use the relative state values of the original periodic SDP. An optimal policy is derived by SDP. The structure of optimal policies is investigated by simulation. Next to its stationary results, as reported before, the combination of SDP and simulation so becomes of even more practical value to blood bank managers. Results show how outdating or product waste of blood platelets can be reduced from over 15% to 1% or even less, while maintaining shortage at a very low level.

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M3 - Chapter

SN - 978-3-319-47764-0

T3 - International Series in Operations Research

SP - 293

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A2 - van Dijk, Nico M.

PB - Springer

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ER -

Haijema R, van Dijk NM, van der Wal J. Blood platelet inventory management. In Boucherie RJ, van Dijk NM, editors, Markov Decision Processes in Practice. Cham: Springer. 2017. p. 293-317. (International Series in Operations Research). https://doi.org/10.1007/978-3-319-47766-4_10