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Scheduling Jobs on Unreliable Machines Subject to Linear Risk

Author

Listed:
  • Alessandro Agnetis

    (Dipartimento di Ingegneria dell’Informazione e Scienze Matematiche, Università di Siena, 53100 Siena, Italy)

  • Ilaria Salvadori

    (Dipartimento di Ingegneria dell’Informazione e Scienze Matematiche, Università di Siena, 53100 Siena, Italy)

Abstract

Background : This paper addresses a new class of scheduling problems in the context of machines subject to (unrecoverable) interruptions; i.e., when a machine fails, the current and subsequently scheduled work on that machine is lost. Each job has a certain processing time and a reward that is attained if the job is successfully completed. Methods : For the failure process, we considered the linear risk model, according to which the probability of machine failure is uniform across a certain time horizon. Results : We analyzed both the situation in which the set of jobs is given, and that in which jobs must be selected from a pool of jobs, at a certain selection cost. Conclusions : We characterized the complexity of various problems, showing both hardness results and polynomial algorithms, and pointed out some open problems.

Suggested Citation

  • Alessandro Agnetis & Ilaria Salvadori, 2025. "Scheduling Jobs on Unreliable Machines Subject to Linear Risk," Logistics, MDPI, vol. 9(4), pages 1-18, November.
    • Handle: RePEc:gam:jlogis:v:9:y:2025:i:4:p:157-:d:1787290
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