Scheduling Jobs on Unreliable Machines Subject to Linear Risk

Alessandro Agnetis and Ilaria Salvadori ()
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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

Logistics, 2025, vol. 9, issue 4, 1-18

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.

Keywords: scheduling; unrecoverable interruptions; unreliable machines; job selection; computational complexity; greedy algorithm (search for similar items in EconPapers)
JEL-codes: L8 L80 L81 L86 L87 L9 L90 L91 L92 L93 L98 L99 M1 M10 M11 M16 M19 R4 R40 R41 R49 (search for similar items in EconPapers)
Date: 2025
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