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Scheduling maintenance and semiresumable jobs on a single machine

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  • Gregory H. Graves
  • Chung‐Yee Lee

Abstract

The majority of scheduling literature assumes that the machines are available at all times. In this paper, we study single machine scheduling problems where the machine maintenance must be performed within certain intervals and hence the machine is not available during the maintenance periods. We also assume that if a job is not processed to completion before the machine is stopped for maintenance, an additional setup is necessary when the processing is resumed. Our purpose is to schedule the maintenance and jobs to minimize some performance measures. The objective functions that we consider are minimizing the total weighted job completion times and minimizing the maximum lateness. In both cases, maintenance must be performed within a fixed period T, and the time for the maintenance is a decision variable. In this paper, we study two scenarios concerning the planning horizon. First, we show that, when the planning horizon is long in relation to T, the problem with either objective function is NP‐complete, and we present pseudopolynomial time dynamic programming algorithms for both objective functions. In the second scenario, the planning horizon is short in relation to T. However, part of the period T may have elapsed before we schedule any jobs in this planning horizon, and the remaining time before the maintenance is shorter than the current planning horizon. Hence we must schedule one maintenance in this planning horizon. We show that the problem of minimizing the total weighted completion times in this scenario is NP‐complete, while the shortest processing time (SPT) rule and the earliest due date (EDD) rule are optimal for the total completion time problem and the maximum lateness problem respectively. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 845–863, 1999

Suggested Citation

  • Gregory H. Graves & Chung‐Yee Lee, 1999. "Scheduling maintenance and semiresumable jobs on a single machine," Naval Research Logistics (NRL), John Wiley & Sons, vol. 46(7), pages 845-863, October.
    • Handle: RePEc:wly:navres:v:46:y:1999:i:7:p:845-863
    DOI: 10.1002/(SICI)1520-6750(199910)46:73.0.CO;2-#
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    References listed on IDEAS

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    Citations

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    1. J-J Wang & J-B Wang & F Liu, 2011. "Parallel machines scheduling with a deteriorating maintenance activity," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(10), pages 1898-1902, October.
    2. Behrooz Shahbazi & Seyed Habib A. Rahmati, 2021. "Developing a Flexible Manufacturing Control System Considering Mixed Uncertain Predictive Maintenance Model: a Simulation-Based Optimization Approach," SN Operations Research Forum, Springer, vol. 2(4), pages 1-43, December.
    3. Yarlin Kuo & Zi‐Ann Chang, 2007. "Integrated production scheduling and preventive maintenance planning for a single machine under a cumulative damage failure process," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(6), pages 602-614, September.
    4. A. Beynaghi & F. Moztarzadeh & A. Shahmardan & R. Alizadeh & J. Salimi & M. Mozafari, 2019. "Makespan minimization for batching work and rework process on a single facility with an aging effect: a hybrid meta-heuristic algorithm for sustainable production management," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 33-45, January.
    5. Koulamas, Christos & Kyparisis, George J., 2023. "A classification of dynamic programming formulations for offline deterministic single-machine scheduling problems," European Journal of Operational Research, Elsevier, vol. 305(3), pages 999-1017.
    6. Seyed Habib A. Rahmati & Abbas Ahmadi & Kannan Govindan, 2018. "A novel integrated condition-based maintenance and stochastic flexible job shop scheduling problem: simulation-based optimization approach," Annals of Operations Research, Springer, vol. 269(1), pages 583-621, October.
    7. Maciej Drozdowski & Florian Jaehn & Radosław Paszkowski, 2017. "Scheduling Position-Dependent Maintenance Operations," Operations Research, INFORMS, vol. 65(6), pages 1657-1677, December.
    8. Detienne, Boris, 2014. "A mixed integer linear programming approach to minimize the number of late jobs with and without machine availability constraints," European Journal of Operational Research, Elsevier, vol. 235(3), pages 540-552.
    9. Deng, Qichen & Santos, Bruno F. & Curran, Richard, 2020. "A practical dynamic programming based methodology for aircraft maintenance check scheduling optimization," European Journal of Operational Research, Elsevier, vol. 281(2), pages 256-273.
    10. K. H. Adjallah & K. P. Adzakpa, 2007. "Minimizing maintenance cost involving flow-time and tardiness penalty with unequal release dates," Journal of Risk and Reliability, , vol. 221(1), pages 57-65, March.
    11. Boccia, Maurizio & Masone, Adriano & Sterle, Claudio & Murino, Teresa, 2023. "The parallel AGV scheduling problem with battery constraints: A new formulation and a matheuristic approach," European Journal of Operational Research, Elsevier, vol. 307(2), pages 590-603.
    12. Kerem Bülbül & Safia Kedad-Sidhoum & Halil Şen, 2019. "Single-machine common due date total earliness/tardiness scheduling with machine unavailability," Journal of Scheduling, Springer, vol. 22(5), pages 543-565, October.
    13. M. A. Kubzin & V. A. Strusevich, 2006. "Planning Machine Maintenance in Two-Machine Shop Scheduling," Operations Research, INFORMS, vol. 54(4), pages 789-800, August.

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