Spare parts inventory control under a fixed-term contract with a long-down constraint

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We are interested in service contracts for spare parts. We introduce a new performance measure that limits the number of deliveries that are later than an agreed threshold during the contract period. We consider a single item, single location stockpoint serving multiple systems where demand is satisfied in an alternative way if the stockpoint is out of stock. Using a finite horizon Markov decision process, we characterize the optimal spare parts inventory policy for meeting the contract at minimum costs. We perform a numerical study to show the performance of the optimal policy in comparison to heuristics commonly used in practice. Our results show that the average optimality gap of those heuristics varies from 6.4% to 175%. The maximum optimality gaps are very high for all three heuristics. This shows that important savings can be made when taking into account the actual contract performance and the remaining contract duration in stocking decisions.
TaalEngels
Pagina's123-137
TijdschriftInternational Journal of Production Economics
Volume219
DOI's
StatusGepubliceerd - 2020

Vingerafdruk

Inventory control
Fixed-term contracts
Heuristics
Spare parts
Optimality
Costs

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    title = "Spare parts inventory control under a fixed-term contract with a long-down constraint",
    abstract = "We are interested in service contracts for spare parts. We introduce a new performance measure that limits the number of deliveries that are later than an agreed threshold during the contract period. We consider a single item, single location stockpoint serving multiple systems where demand is satisfied in an alternative way if the stockpoint is out of stock. Using a finite horizon Markov decision process, we characterize the optimal spare parts inventory policy for meeting the contract at minimum costs. We perform a numerical study to show the performance of the optimal policy in comparison to heuristics commonly used in practice. Our results show that the average optimality gap of those heuristics varies from 6.4{\%} to 175{\%}. The maximum optimality gaps are very high for all three heuristics. This shows that important savings can be made when taking into account the actual contract performance and the remaining contract duration in stocking decisions.",
    keywords = "Spare parts inventory, Service measure, Markov decision process, Optimal policies, Discrete convexity",
    author = "Douniel Lamghari-Idrissi and Rob Basten and {van Houtum}, Geert-Jan",
    year = "2020",
    doi = "10.1016/j.ijpe.2019.05.023",
    language = "English",
    volume = "219",
    pages = "123--137",
    journal = "International Journal of Production Economics",
    issn = "0925-5273",
    publisher = "Elsevier",

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    TY - JOUR

    T1 - Spare parts inventory control under a fixed-term contract with a long-down constraint

    AU - Lamghari-Idrissi,Douniel

    AU - Basten,Rob

    AU - van Houtum,Geert-Jan

    PY - 2020

    Y1 - 2020

    N2 - We are interested in service contracts for spare parts. We introduce a new performance measure that limits the number of deliveries that are later than an agreed threshold during the contract period. We consider a single item, single location stockpoint serving multiple systems where demand is satisfied in an alternative way if the stockpoint is out of stock. Using a finite horizon Markov decision process, we characterize the optimal spare parts inventory policy for meeting the contract at minimum costs. We perform a numerical study to show the performance of the optimal policy in comparison to heuristics commonly used in practice. Our results show that the average optimality gap of those heuristics varies from 6.4% to 175%. The maximum optimality gaps are very high for all three heuristics. This shows that important savings can be made when taking into account the actual contract performance and the remaining contract duration in stocking decisions.

    AB - We are interested in service contracts for spare parts. We introduce a new performance measure that limits the number of deliveries that are later than an agreed threshold during the contract period. We consider a single item, single location stockpoint serving multiple systems where demand is satisfied in an alternative way if the stockpoint is out of stock. Using a finite horizon Markov decision process, we characterize the optimal spare parts inventory policy for meeting the contract at minimum costs. We perform a numerical study to show the performance of the optimal policy in comparison to heuristics commonly used in practice. Our results show that the average optimality gap of those heuristics varies from 6.4% to 175%. The maximum optimality gaps are very high for all three heuristics. This shows that important savings can be made when taking into account the actual contract performance and the remaining contract duration in stocking decisions.

    KW - Spare parts inventory

    KW - Service measure

    KW - Markov decision process

    KW - Optimal policies

    KW - Discrete convexity

    U2 - 10.1016/j.ijpe.2019.05.023

    DO - 10.1016/j.ijpe.2019.05.023

    M3 - Article

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    SP - 123

    EP - 137

    JO - International Journal of Production Economics

    T2 - International Journal of Production Economics

    JF - International Journal of Production Economics

    SN - 0925-5273

    ER -