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Parallel-machine scheduling with machine-dependent maintenance periodic recycles

Author

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  • Li, Guo
  • Liu, Mengqi
  • Sethi, Suresh P.
  • Xu, Dehua

Abstract

Parallel machine structure is very common in modern production systems. Its performance sometimes has a decisive impact on the whole productivity. In this paper, we consider a parallel-machine scheduling problem where each machine is subject to periodic maintenance. Instead of assuming all the machines have the same maintenance periodic cycle, we assume the maintenance periodic cycles are machine-dependent. The objective is to schedule all the jobs to the machines such that the makespan is minimized. We first provide computational complexity and non-approximability analyses of the problem and then present two mathematical programming models to tackle small-sized instances. Thereafter, we present a worst-case analysis of the classical LPT and LS algorithms for the problem. Then we propose two improved heuristic algorithms based on some observations of large-sized instances. In order to evaluate the performance of the heuristic algorithms, we resort to a lower bound of the optimal makespan, and find that it has a very interesting characteristic. Numerical experiments show that the improved heuristic algorithm MLPT improves the objective value of the LPT schedule by about 6.75% on average and that the MLPT heuristic algorithm has an average-case relative error less than 1.57% for all combinations of instances, which means that it is very suitable for real world applications.

Suggested Citation

  • Li, Guo & Liu, Mengqi & Sethi, Suresh P. & Xu, Dehua, 2017. "Parallel-machine scheduling with machine-dependent maintenance periodic recycles," International Journal of Production Economics, Elsevier, vol. 186(C), pages 1-7.
    • Handle: RePEc:eee:proeco:v:186:y:2017:i:c:p:1-7
    DOI: 10.1016/j.ijpe.2017.01.014
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    References listed on IDEAS

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    1. Xu, Dehua & Wan, Long & Liu, Aihua & Yang, Dar-Li, 2015. "Single machine total completion time scheduling problem with workload-dependent maintenance duration," Omega, Elsevier, vol. 52(C), pages 101-106.
    2. Chen, Wen-Jinn, 2009. "Minimizing number of tardy jobs on a single machine subject to periodic maintenance," Omega, Elsevier, vol. 37(3), pages 591-599, June.
    3. Sun, Kaibiao & Li, Hongxing, 2010. "Scheduling problems with multiple maintenance activities and non-preemptive jobs on two identical parallel machines," International Journal of Production Economics, Elsevier, vol. 124(1), pages 151-158, March.
    4. Yin, Yunqiang & Cheng, T.C.E. & Wang, Du-Juan, 2016. "Rescheduling on identical parallel machines with machine disruptions to minimize total completion time," European Journal of Operational Research, Elsevier, vol. 252(3), pages 737-749.
    5. Wang, Xiuli & Cheng, T.C.E., 2015. "A heuristic for scheduling jobs on two identical parallel machines with a machine availability constraint," International Journal of Production Economics, Elsevier, vol. 161(C), pages 74-82.
    6. Ma, Ran & Yuan, Jinjiang, 2014. "Online tradeoff scheduling on a single machine to minimize makespan and total weighted completion time," International Journal of Production Economics, Elsevier, vol. 158(C), pages 114-119.
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    Cited by:

    1. Michael Geurtsen & Jelle Adan & Alp Akçay, 2024. "Integrated maintenance and production scheduling for unrelated parallel machines with setup times," Flexible Services and Manufacturing Journal, Springer, vol. 36(3), pages 1046-1079, September.
    2. Li, Guo & Li, Na & Sambandam, Narayanasamy & Sethi, Suresh P. & Zhang, Faping, 2018. "Flow shop scheduling with jobs arriving at different times," International Journal of Production Economics, Elsevier, vol. 206(C), pages 250-260.
    3. Song Jiu, 2021. "A two-phase approach for integrating preventive maintenance with production and delivery in an unreliable coal mine," Journal of Heuristics, Springer, vol. 27(6), pages 991-1020, December.
    4. Shastitko, Anastasia (Шаститко, Анастасия), 2018. "Application of the Conclusions of the Behavioral Economy to the Behavior of Civil Servants: Methodological Aspects [Применение Выводов Поведенческой Экономики К Поведению Государственных Служащих: ," Working Papers 031823, Russian Presidential Academy of National Economy and Public Administration.
    5. Hanane Krim & Nicolas Zufferey & Jean-Yves Potvin & Rachid Benmansour & David Duvivier, 2022. "Tabu search for a parallel-machine scheduling problem with periodic maintenance, job rejection and weighted sum of completion times," Journal of Scheduling, Springer, vol. 25(1), pages 89-105, February.
    6. Nasini, Stefano & Nessah, Rabia, 2022. "A multi-machine scheduling solution for homogeneous processing: Asymptotic approximation and applications," International Journal of Production Economics, Elsevier, vol. 251(C).
    7. Wieslaw Kubiak & Yanling Feng & Guo Li & Suresh P. Sethi & Chelliah Sriskandarajah, 2020. "Efficient algorithms for flexible job shop scheduling with parallel machines," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(4), pages 272-288, June.
    8. Hanane Krim & Rachid Benmansour & David Duvivier & Daoud Aït-Kadi & Said Hanafi, 2020. "Heuristics for the single machine weighted sum of completion times scheduling problem with periodic maintenance," Computational Optimization and Applications, Springer, vol. 75(1), pages 291-320, January.
    9. Feng, Yanling & Li, Guo & Sethi, Suresh P., 2018. "A three-layer chromosome genetic algorithm for multi-cell scheduling with flexible routes and machine sharing," International Journal of Production Economics, Elsevier, vol. 196(C), pages 269-283.
    10. Feng, Hanxin & Xi, Lifeng & Xiao, Lei & Xia, Tangbin & Pan, Ershun, 2018. "Imperfect preventive maintenance optimization for flexible flowshop manufacturing cells considering sequence-dependent group scheduling," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 218-229.

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