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A genetic algorithm methodology for complex scheduling problems

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  • Bryan A. Norman
  • James C. Bean

Abstract

This paper considers the scheduling problem to minimize total tardiness given multiple machines, ready times, sequence dependent setups, machine downtime and scarce tools. We develop a genetic algorithm based on random keys representation, elitist reproduction, Bernoulli crossover and immigration type mutation. Convergence of the algorithm is proved. We present computational results on data sets from the auto industry. To demonstrate robustness of the approach, problems from the literature of different structure are solved by essentially the same algorithm. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 199–211, 1999

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  • Bryan A. Norman & James C. Bean, 1999. "A genetic algorithm methodology for complex scheduling problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 46(2), pages 199-211, March.
    • Handle: RePEc:wly:navres:v:46:y:1999:i:2:p:199-211
    DOI: 10.1002/(SICI)1520-6750(199903)46:23.0.CO;2-L
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    References listed on IDEAS

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    1. James C. Bean & John R. Birge & John Mittenthal & Charles E. Noon, 1991. "Matchup Scheduling with Multiple Resources, Release Dates and Disruptions," Operations Research, INFORMS, vol. 39(3), pages 470-483, June.
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    3. Robert H. Storer & S. David Wu & Renzo Vaccari, 1992. "New Search Spaces for Sequencing Problems with Application to Job Shop Scheduling," Management Science, INFORMS, vol. 38(10), pages 1495-1509, October.
    4. Grabowski, J. & Nowicki, E. & Zdrzalka, S., 1986. "A block approach for single-machine scheduling with release dates and due dates," European Journal of Operational Research, Elsevier, vol. 26(2), pages 278-285, August.
    5. Joseph Adams & Egon Balas & Daniel Zawack, 1988. "The Shifting Bottleneck Procedure for Job Shop Scheduling," Management Science, INFORMS, vol. 34(3), pages 391-401, March.
    6. James C. Bean, 1994. "Genetic Algorithms and Random Keys for Sequencing and Optimization," INFORMS Journal on Computing, INFORMS, vol. 6(2), pages 154-160, May.
    7. Fred Glover, 1990. "Tabu Search—Part II," INFORMS Journal on Computing, INFORMS, vol. 2(1), pages 4-32, February.
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    Cited by:

    1. Jacomine Grobler & Andries Engelbrecht & Schalk Kok & Sarma Yadavalli, 2010. "Metaheuristics for the multi-objective FJSP with sequence-dependent set-up times, auxiliary resources and machine down time," Annals of Operations Research, Springer, vol. 180(1), pages 165-196, November.
    2. Alper Türkyılmaz & Özlem Şenvar & İrem Ünal & Serol Bulkan, 2020. "A research survey: heuristic approaches for solving multi objective flexible job shop problems," Journal of Intelligent Manufacturing, Springer, vol. 31(8), pages 1949-1983, December.
    3. Hongmin Li & Woonghee T. Huh & Matheus C. Sampaio & Naiping Keng, 2021. "Planning Production and Equipment Qualification under High Process Flexibility," Production and Operations Management, Production and Operations Management Society, vol. 30(10), pages 3369-3390, October.
    4. Alice E. Smith, 2023. "Note from the Editor," INFORMS Journal on Computing, INFORMS, vol. 35(4), pages 711-712, July.

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