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Plant shutdown maintenance workforce team assignment and job scheduling

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Abstract

An important and challenging real-life problem is considered, involving workforce assignment and job scheduling for shutdown maintenance in a large oil refinery. A limited number of maintenance employees must be divided into several teams that work in parallel on different maintenance tasks. The objective is to minimize the shutdown cost by minimizing the total shutdown period, i.e., the time to complete all the maintenance tasks. Different team sizes are possible, and the size of the given team determines the speed of finishing the assigned maintenance tasks. Constraints include job availability (arrival) times, and precedence relations between different jobs. This problem can be considered as a resource-constrained parallel-machine scheduling problem, in which the objective is to minimize the makespan, and both the number and the speeds of the machines are decision variables. An integer programming model of this problem is formulated, but optimum solution is difficult because the problem is NP-hard. Therefore, a two-stage heuristic solution algorithm is developed and shown to be quite effective for solving this problem.

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References

  • Alfares, H. K., Lilly, M. T., & Emovon, I. (2007). Maintenance staff scheduling at Afam power station. Industrial Engineering & Management Systems, 6(1), 22–27.

    Google Scholar 

  • Al-Turki, U., Duffuaa, S., & Bendaya, M. (2019). Trends in turnaround maintenance planning: Literature review. Journal of Quality in Maintenance Engineering, 25(2), 253–271.

    Article  Google Scholar 

  • Blazewicz, J., Lenstra, J. K., & Kan, A. R. (1983). Scheduling subject to resource constraints: Classification and complexity. Discrete Applied Mathematics, 5(1), 11–24.

    Article  Google Scholar 

  • Çanakoğlu, E., & Muter, İ. (2020). Identical parallel machine scheduling with discrete additional resource and an application in audit scheduling. International Journal of Production Research, 59(17), 5321–5336.

    Article  Google Scholar 

  • Castro, P. M., Grossmann, I. E., Veldhuizen, P., & Esplin, D. (2014). Optimal maintenance scheduling of a gas engine power plant using generalized disjunctive programming. AIChE Journal, 60(6), 2083–2097.

    Article  Google Scholar 

  • Cheng, T. C. E., & Sin, C. C. S. (1990). A state-of-the-art review of parallel-machine scheduling research. European Journal of Operational Research, 47(3), 271–292.

    Article  Google Scholar 

  • Daniels, R. L., Hua, S. Y., & Webster, S. (1999). Heuristics for parallel-machine flexible-resource scheduling problems with unspecified job assignment. Computers & Operations Research, 26(2), 143–155.

    Article  Google Scholar 

  • Das Adhikary, D., Bose, G. K., Jana, D. K., Bose, D., & Mitra, S. (2016). Availability and cost-centered preventive maintenance scheduling of continuous operating series systems using multi-objective genetic algorithm: A case study. Quality Engineering, 28(3), 352–357.

    Article  Google Scholar 

  • Edis, E. B., Oguz, C., & Ozkarahan, I. (2013). Parallel machine scheduling with additional resources: Notation, classification, models and solution methods. European Journal of Operational Research, 230(3), 449–463.

    Article  Google Scholar 

  • Fanjul-Peyro, L., Perea, F., & Ruiz, R. (2017). Models and matheuristics for the unrelated parallel machine scheduling problem with additional resources. European Journal of Operational Research, 260(2), 482–493.

    Article  Google Scholar 

  • Fırat, M., & Hurkens, C. A. J. (2012). An improved MIP-based approach for a multi-skill workforce scheduling problem. Journal of Scheduling, 15(3), 363–380.

    Article  Google Scholar 

  • Graham, R. L., Lawler, E. L., Lenstra, J. K., & Kan, A. R. (1979). Optimization and approximation in deterministic sequencing and scheduling: a survey. In Annals of Discrete Mathematics (Vol. 5, pp. 287–326). Elsevier.

  • Ighravwe, D. E., & Oke, S. A. (2014). A non-zero integer non-linear programming model for maintenance workforce sizing. International Journal of Production Economics, 150, 204–214.

    Article  Google Scholar 

  • Koochaki, J., Bokhorst, J. A., Wortmann, H., & Klingenberg, W. (2013). The influence of condition-based maintenance on workforce planning and maintenance scheduling. International Journal of Production Research, 51(8), 2339–2351.

    Article  Google Scholar 

  • Kovacs, A. A., Parragh, S. N., Doerner, K. F., & Hartl, R. F. (2012). Adaptive large neighborhood search for service technician routing and scheduling problems. Journal of Scheduling, 15(5), 579–600.

    Article  Google Scholar 

  • Lusby, R., Muller, L. F., & Petersen, B. (2013). A solution approach based on Benders decomposition for the preventive maintenance scheduling problem of a stochastic large-scale energy system. Journal of Scheduling, 16(6), 605–628.

    Article  Google Scholar 

  • Matsuoka, S., & Muraki, M. (2007). Short-term maintenance scheduling for utility systems. Journal of Quality in Maintenance Engineering, 13(3), 228–240.

    Article  Google Scholar 

  • Mazzola, J. B., & Neebe, A. W. (1986). Resource-constrained assignment scheduling. Operations Research, 34(4), 560–572.

    Article  Google Scholar 

  • Mokotoff, E. (2001). Parallel machine scheduling problems: A survey. Asia-Pacific Journal of Operational Research, 18(2), 193–242.

    Google Scholar 

  • OpenSolver Version 2.9.3. http://opensolver.org. Accessed July 2021.

  • Różycki, R., & Węglarz, J. (2014). Power-aware scheduling of preemptable jobs on identical parallel processors to minimize makespan. Annals of Operations Research, 213(1), 235–252.

    Article  Google Scholar 

  • Ruiz-Torres, A. J., & Centeno, G. (2007). Scheduling with flexible resources in parallel workcenters to minimize maximum completion time. Computers & Operations Research, 34(1), 48–69.

    Article  Google Scholar 

  • Safaei, N., Banjevic, D., & Jardine, A. K. (2011). Bi-objective workforce-constrained maintenance scheduling: A case study. Journal of the Operational Research Society, 62(6), 1005–1018.

    Article  Google Scholar 

  • Schulz, E. P., Bandoni, J. A., & Diaz, M. S. (2006). Optimal shutdown policy for maintenance of cracking furnaces in ethylene plants. Industrial & Engineering Chemistry Research, 45(8), 2748–2757.

    Article  Google Scholar 

  • Sun, H. F., Liu, X. D., & Hou, W. (2014). Research of parallel machine scheduling with flexible resources based on nested partition method. Applied Mechanics and Materials, 459, 488–493.

    Article  Google Scholar 

  • Unlu, Y., & Mason, S. J. (2010). Evaluation of mixed integer programming formulations for non-preemptive parallel machine scheduling problems. Computers & Industrial Engineering, 58(4), 785–800.

    Article  Google Scholar 

  • Yare, Y., & Venayagamoorthy, G. K. (2010). Optimal maintenance scheduling of generators using multiple swarms-MDPSO framework. Engineering Applications of Artificial Intelligence, 23(6), 895–910.

    Article  Google Scholar 

  • Zheng, X. L., & Wang, L. (2018). A collaborative multiobjective fruit fly optimization algorithm for the resource constrained unrelated parallel machine green scheduling problem. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48(5), 790–800.

    Article  Google Scholar 

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  1. Systems Engineering Department, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran, 31261, Saudi Arabia

    Hesham K. Alfares

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  1. Hesham K. Alfares
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Alfares, H.K. Plant shutdown maintenance workforce team assignment and job scheduling. J Sched 25, 321–338 (2022). https://doi.org/10.1007/s10951-021-00718-2

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