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Predictive/reactive scheduling with controllable processing times and earliness-tardiness penalties

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  • Ayten Turkcan
  • M. Akturk
  • Robert Storer

Abstract

In this study, a machine scheduling problem with controllable processing times in a parallel-machine environment is considered. The objectives are the minimization of manufacturing cost, which is a convex function of processing time, and total weighted earliness and tardiness. It is assumed that parts have job-dependent earliness and tardiness penalties and distinct due dates, and idle time is allowed. The problem is formulated as a time-indexed integer programming model with discrete processing time alternatives for each part. A linear-relaxation-based algorithm is used to assign the parts to the machines and to find a sequence on each machine. A non-linear programming model is proposed to find the optimal starting and processing times of the parts for a given sequence. The proposed non-linear programming model is converted to a minimum-cost network flow model by piecewise linearization of the convex manufacturing cost in the objective function. The proposed method is used to find initial schedules in predictive scheduling. The proposed models are revised to incorporate a stability measure for reacting to unexpected disruptions such as machine breakdown, arrival of a new job, delay in the arrival or the shortage of materials in reactive scheduling.

Suggested Citation

  • Ayten Turkcan & M. Akturk & Robert Storer, 2009. "Predictive/reactive scheduling with controllable processing times and earliness-tardiness penalties," IISE Transactions, Taylor & Francis Journals, vol. 41(12), pages 1080-1095.
    • Handle: RePEc:taf:uiiexx:v:41:y:2009:i:12:p:1080-1095
    DOI: 10.1080/07408170902905995
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    Cited by:

    1. Iwona Paprocka & Bożena Skołud, 2017. "A hybrid multi-objective immune algorithm for predictive and reactive scheduling," Journal of Scheduling, Springer, vol. 20(2), pages 165-182, April.
    2. Ali Kordmostafapour & Javad Rezaeian & Iraj Mahdavi & Mahdi Yar Farjad, 2022. "Scheduling unrelated parallel machine problem with multi-mode processing times and batch delivery cost," OPSEARCH, Springer;Operational Research Society of India, vol. 59(4), pages 1438-1470, December.
    3. Borgonjon, Tessa & Maenhout, Broos, 2022. "An exact approach for the personnel task rescheduling problem with task retiming," European Journal of Operational Research, Elsevier, vol. 296(2), pages 465-484.
    4. Ajay Surendrarao Bhongade & Prakash Manohar Khodke & Ateekh Ur Rehman & Manoj Dattatray Nikam & Prathamesh Dattatray Patil & Pramod Suryavanshi, 2023. "Managing Disruptions in a Flow-Shop Manufacturing System," Mathematics, MDPI, vol. 11(7), pages 1-22, April.

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