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Single-machine rescheduling problems with learning effect under disruptions

  • * Corresponding author

    * Corresponding author
The research is supported partially by the National Natural Science Foundation Committee of China grant 71571050,71502100,71401044.
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  • Rescheduling in production planning means to schedule the sequenced jobs again together with a set of new arrived jobs so as to generate a new feasible schedule, which creates disruptions to any job between the original and adjusted position. In this paper, we study rescheduling problems with learning effect under disruption constraints to minimize several classical objectives, where learning effect means that the workers gain experience during the process of operation and make the actual processing time of jobs shorter than their normal processing time. The objectives are to find optimal sequences to minimize the makespan and the total completion time under a limit of the disruptions from the original schedule. For the considered objectives under a single disruption constraint or a disruption cost constraint, we propose polynomial-time algorithms and pseudo-polynomial time algorithms, respectively.

    Mathematics Subject Classification: Primary: 90B35; Secondary: 90C26.


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  • [1] M. J. Anzanello and F. S. Fogliatto, Learning curve models and applications: Literature review and research directions, International Journal of Industrial Ergonomics, 41 (2011), 573-583.  doi: 10.1016/j.ergon.2011.05.001.
    [2] J. P. Arnaout, Rescheduling of parallel machines with stochastic processing and setup times, Journal of Manufacturing Systems, 33 (2014), 376-384.  doi: 10.1016/j.jmsy.2014.02.003.
    [3] M. Azizoglu and O. Alagoz, Parallel-machine rescheduling with machine disruptions, IIE Transactions, 37 (2007), 1113-1118.  doi: 10.1080/07408170500288133.
    [4] A. Bachman and A. Janiak, Scheduling job with position-dependent processing times, Journal of the Operational Research Society, 55 (2004), 257-264. 
    [5] D. Biskup, Single-machine scheduling with learning considerations, European Journal of Operational Research, 115 (1999), 173-178.  doi: 10.1016/S0377-2217(98)00246-X.
    [6] D. Biskup, A state-of-the-art review on scheduling with learning effects, European Journal of Operational Research, 188 (2008), 315-329.  doi: 10.1016/j.ejor.2007.05.040.
    [7] M. B. Cheng and S. J. Sun, The single-machine scheduling problems with deteriorating jobs and learning effect, Zhejiang Univ. Science A, 7 (2006), 597-601. 
    [8] M. B. ChengP. R. TadikamallaJ. Shang and B. X. Zhang, Single machine scheduling problems with exponentially time-dependent learning effects, Journal of Manufacturing Systems, 34 (2015), 60-65.  doi: 10.1016/j.jmsy.2014.11.001.
    [9] Y. Chiu and C. J. Shih, Rescheduling strategies for integrating rush orders with preventive maintenance in a two-machine flow shop, International Journal of Production Research, 50 (2011), 5783-5794.  doi: 10.1080/00207543.2011.627887.
    [10] J. A. FilarP. ManyemD. M. Panton and K. White, A model for adaptive rescheduling of flights in emergencies, Journal of Industrial and Management Optimization, 3 (2007), 335-356.  doi: 10.3934/jimo.2007.3.335.
    [11] N. G. Hall and C. N. Potts, Rescheduling for new orders, Operations Research, 52 (2004), 440-453.  doi: 10.1287/opre.1030.0101.
    [12] N. G. Hall and C. N. Potts, Rescheduling for Job Unavailability, Operations Research, 58 (2010), 746-755.  doi: 10.1287/opre.1090.0751.
    [13] H. HoogeveenC. Lent and V. Tkindtal, Rescheduling for new orders on a single machine with setup times, European Journal of Operational Research, 223 (2012), 40-46.  doi: 10.1016/j.ejor.2012.05.046.
    [14] K. KatragjiniE. Vallada and R. Ruiz, Flow shop rescheduling under different types of disruption, International Journal of Production Research, 51 (2013), 780-797. 
    [15] L. Liu and H. Zhou, On the identical parallel-machine rescheduling with job rework disruption, Computers & Industrial Engineering, 66 (2013), 186-198.  doi: 10.1016/j.cie.2013.02.018.
    [16] Z. Liu and K. Ro Young, Rescheduling for machine disruption to minimize makespan and maximum lateness, Journal of Scheduling, 17 (2014), 339-352.  doi: 10.1007/s10951-014-0372-2.
    [17] G. Mosheiov, Scheduling problems with learning effect, European Journal of Operational Research, 132 (2001), 687-693.  doi: 10.1016/S0377-2217(00)00175-2.
    [18] M. Ozlen and M. Azizoglu, Rescheduling unrelated parallel machines with total flow time and total disruption cost criteria, Journal of the Operational Research Society, 62 (2011), 152-164.  doi: 10.1057/jors.2009.157.
    [19] L. L. SunF. J. LuanY. Ying and K. Mao, Rescheduling optimization of steelmaking-continuous casting process based on the Lagrangian heuristic algorithm, Journal of Industrial and Management Optimization, 13 (2017), 1431-1448.  doi: 10.3934/jimo.2016081.
    [20] B. Vahedi-NouriP. FattahiM. Rohaninejad and R. Tavakkoli-Moghaddam, Minimizing the total completion time on a single machine with the learning effect and multiple availability constraints, Applied Mathematical Modelling, 37 (2013), 3126-3137.  doi: 10.1016/j.apm.2012.07.028.
    [21] J. B. WangM. Q. LiuN. Yin and P. Ji, Scheduling jobs with controllable processing time, truncated job-dependent learning and deterioration effects, Journal of Industrial and Management Optimization, 13 (2017), 1025-1039.  doi: 10.3934/jimo.2016060.
    [22] T. P. Wright, Factors Affecting the Cost of Airplanes, Journal of Aeronautical Sciences, 3 (1936), 122-128.  doi: 10.2514/8.155.
    [23] S. D. Wu, R. H. Storer and P. C. Chang, A rescheduling procedure for manufacturing systems under random disruptions, in: G. Fandel, T. Gulledge, A. Jone (Eds. ), New Directions for Operations Research in Manufacturing, Springer, Berlin, Germany, 1992, pp. 292-306. doi: 10.1007/978-3-642-77537-6_18.
    [24] B. B. Yang, Single machine rescheduling with new jobs arrivals and processing time compression, International Journal of Advanced Manufacture Technology, 34 (2007), 378-384.  doi: 10.1007/s00170-006-0590-7.
    [25] Y. Q. YinD. H. XuK. B. Sun and H. X. Li, Some scheduling problems with general position-dependent and time-dependent learning effects, Information Sciences, 179 (2009), 2416-2425.  doi: 10.1016/j.ins.2009.02.015.
    [26] J. J. Yuan and Y. Mu, Rescheduling with release dates to minimize makespan under a limit on the maximum sequence disruption, European Journal of Operational Research, 182 (2007), 936-944. 
    [27] L. ZhangL. Gao and X. Li, A hybrid intelligent algorithm and rescheduling technique for job shop scheduling problems with disruptions, International Journal of Advanced Manufacturing Technology, 65 (2013), 1141-1156. 
    [28] C. Zhao and H. Tang, Rescheduling problems with deteriorating jobs under disruptions, Applied Mathematical Modelling, 34 (2010), 238-243.  doi: 10.1016/j.apm.2009.03.037.
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