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Cost allocation in inventory pools of spare parts with service-differentiated demand classes

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  • M. Guajardo
  • M. Rönnqvist

Abstract

Holding inventory of spare parts is critical to assure safety and production. In order to save costs, different producers may collaborate through an inventory pool. We consider an inventory pool of spare parts, subject to a service level constraint, where the members of the pool may have different target service levels, so that they represent different demand classes. The pool is implemented either by round-up or rationing policies. The members should agree on how to share the costs. Based on cooperative game theory concepts, we show the important effects that different targets can have in the core stability for this problem. We perform a computational study in a large number of instances, providing insights on the emptiness of the core and the performance of seven allocation methods. We also propose the novel Minimum Deviation from Service Level Referential Cost Method (MIND). This method looks for a stable allocation such that the maximum difference between a cost allocated to a player and its service level referential cost is minimised. The MIND allocation is the solution to a linear programming model and is core guaranteed, in the sense that if the core is not empty, the allocation belongs to the core.

Suggested Citation

  • M. Guajardo & M. Rönnqvist, 2015. "Cost allocation in inventory pools of spare parts with service-differentiated demand classes," International Journal of Production Research, Taylor & Francis Journals, vol. 53(1), pages 220-237, January.
  • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:1:p:220-237
    DOI: 10.1080/00207543.2014.948577
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    Citations

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    Cited by:

    1. Basso, Franco & Guajardo, Mario & Varas, Mauricio, 2020. "Collaborative job scheduling in the wine bottling process," Omega, Elsevier, vol. 91(C).
    2. Mauricio Varas & Franco Basso & Paul Bosch & Juan Pablo Contreras & Raúl Pezoa, 2022. "A horizontal collaborative approach for planning the wine grape harvesting," Operational Research, Springer, vol. 22(5), pages 4965-4998, November.
    3. Westerink-Duijzer, L.E. & Schlicher, L.P.J. & Musegaas, M., 2019. "Fair allocations for cooperation problems in vaccination," Econometric Institute Research Papers EI2019-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Mahdavi, Mojtaba & Olsen, Tava Lennon, 2021. "The dual-serving problem: What is the right choice of inventory strategy?," Omega, Elsevier, vol. 103(C).
    5. Schlicher, L.P.J. & Musegaas, M. & Westerink-Duijzer, L.E., 2019. "Resource location games," Econometric Institute Research Papers EI2019-05, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Bikash Koli Dey & Hyesung Seok, 2024. "Intelligent inventory management with autonomation and service strategy," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 307-330, January.
    7. Loe Schlicher & Marco Slikker & Geert‐Jan van Houtum, 2017. "Probabilistic resource pooling games," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(7), pages 531-546, October.
    8. Luis A. Guardiola & Ana Meca & Justo Puerto, 2021. "Enforcing fair cooperation in production-inventory settings with heterogeneous agents," Annals of Operations Research, Springer, vol. 305(1), pages 59-80, October.
    9. Christopher A. Boone & Benjamin T. Hazen & Joseph B. Skipper & Robert E. Overstreet, 2018. "A framework for investigating optimization of service parts performance with big data," Annals of Operations Research, Springer, vol. 270(1), pages 65-74, November.
    10. Lotty E. Westerink‐Duijzer & Loe P. J. Schlicher & Marieke Musegaas, 2020. "Core Allocations for Cooperation Problems in Vaccination," Production and Operations Management, Production and Operations Management Society, vol. 29(7), pages 1720-1737, July.
    11. Basso, Franco & Basso, Leonardo J. & Rönnqvist, Mikael & Weintraub, Andres, 2021. "Coalition formation in collaborative production and transportation with competing firms," European Journal of Operational Research, Elsevier, vol. 289(2), pages 569-581.
    12. Prak, Dennis & Saccani, Nicola & Syntetos, Aris & Teunter, Ruud & Visintin, Filippo, 2017. "The Repair Kit Problem with positive replenishment lead times and fixed ordering costs," European Journal of Operational Research, Elsevier, vol. 261(3), pages 893-902.

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