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

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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.
LanguageEnglish
Pages123-137
JournalInternational Journal of Production Economics
Volume219
DOIs
StatePublished - 2020

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Inventory control
Fixed-term contracts
Heuristics
Spare parts
Optimality
Costs

Keywords

  • Spare parts inventory
  • Service measure
  • Markov decision process
  • Optimal policies
  • Discrete convexity

Cite this

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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",
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language = "English",
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journal = "International Journal of Production Economics",
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AU - Basten,Rob

AU - van Houtum,Geert-Jan

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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.

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