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A memetic algorithm based on a NSGAII scheme for the flexible job-shop scheduling problem

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  • Mariano Frutos
  • Ana Olivera
  • Fernando Tohmé

Abstract

The Flexible Job-Shop Scheduling Problem is concerned with the determination of a sequence of jobs, consisting of many operations, on different machines, satisfying several parallel goals. We introduce a Memetic Algorithm, based on the NSGAII (Non-Dominated Sorting Genetic Algorithm II) acting on two chromosomes, to solve this problem. The algorithm adds, to the genetic stage, a local search procedure (Simulated Annealing). We have assessed its efficiency by running the algorithm on multiple objective instances of the problem. We draw statistics from those runs, which indicate that this Memetic Algorithm yields good and low-cost solutions. Copyright Springer Science+Business Media, LLC 2010

Suggested Citation

  • Mariano Frutos & Ana Olivera & Fernando Tohmé, 2010. "A memetic algorithm based on a NSGAII scheme for the flexible job-shop scheduling problem," Annals of Operations Research, Springer, vol. 181(1), pages 745-765, December.
    • Handle: RePEc:spr:annopr:v:181:y:2010:i:1:p:745-765:10.1007/s10479-010-0751-9
    DOI: 10.1007/s10479-010-0751-9
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    References listed on IDEAS

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    1. 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.
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    4. Andrzej Jaszkiewicz, 2004. "A Comparative Study of Multiple-Objective Metaheuristics on the Bi-Objective Set Covering Problem and the Pareto Memetic Algorithm," Annals of Operations Research, Springer, vol. 131(1), pages 135-158, October.
    5. Cheng-Chung Cheng & Stephen Smith, 1997. "Applying constraint satisfaction techniques to job shop scheduling," Annals of Operations Research, Springer, vol. 70(0), pages 327-357, April.
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    Cited by:

    1. Seyed Habib A. Rahmati & Abbas Ahmadi & Kannan Govindan, 2018. "A novel integrated condition-based maintenance and stochastic flexible job shop scheduling problem: simulation-based optimization approach," Annals of Operations Research, Springer, vol. 269(1), pages 583-621, October.
    2. Jose L. Andrade-Pineda & David Canca & Pedro L. Gonzalez-R & M. Calle, 2020. "Scheduling a dual-resource flexible job shop with makespan and due date-related criteria," Annals of Operations Research, Springer, vol. 291(1), pages 5-35, August.
    3. Ali Hosseinabadi & Hajar Siar & Shahaboddin Shamshirband & Mohammad Shojafar & Mohd Nasir, 2015. "Using the gravitational emulation local search algorithm to solve the multi-objective flexible dynamic job shop scheduling problem in Small and Medium Enterprises," Annals of Operations Research, Springer, vol. 229(1), pages 451-474, June.
    4. 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.
    5. Hanieh Shambayati & Mohsen Shafiei Nikabadi & Sara Saberi & Abbas Mardani, 2024. "A neutrosophic optimization model for supply chain virtualization in the circular economy using the non-dominated sorting genetic algorithm II," Annals of Operations Research, Springer, vol. 342(1), pages 687-723, November.
    6. Simge Yelkenci Kose & Ozcan Kilincci, 2020. "A multi-objective hybrid evolutionary approach for buffer allocation in open serial production lines," Journal of Intelligent Manufacturing, Springer, vol. 31(1), pages 33-51, January.
    7. Dauzère-Pérès, Stéphane & Ding, Junwen & Shen, Liji & Tamssaouet, Karim, 2024. "The flexible job shop scheduling problem: A review," European Journal of Operational Research, Elsevier, vol. 314(2), pages 409-432.

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