IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v181y2010i1p745-76510.1007-s10479-010-0751-9.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-010-0751-9
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-010-0751-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Amaral Armentano, Vinicius & Rigao Scrich, Cintia, 2000. "Tabu search for minimizing total tardiness in a job shop," International Journal of Production Economics, Elsevier, vol. 63(2), pages 131-140, January.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jain, A. S. & Meeran, S., 1999. "Deterministic job-shop scheduling: Past, present and future," European Journal of Operational Research, Elsevier, vol. 113(2), pages 390-434, March.
    2. P Corry & E Kozan, 2004. "Job scheduling with technical constraints," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(2), pages 160-169, February.
    3. Bierwirth, C. & Kuhpfahl, J., 2017. "Extended GRASP for the job shop scheduling problem with total weighted tardiness objective," European Journal of Operational Research, Elsevier, vol. 261(3), pages 835-848.
    4. Pannee Suanpang & Pitchaya Jamjuntr & Kittisak Jermsittiparsert & Phuripoj Kaewyong, 2022. "Tourism Service Scheduling in Smart City Based on Hybrid Genetic Algorithm Simulated Annealing Algorithm," Sustainability, MDPI, vol. 14(23), pages 1-21, December.
    5. Hamed Piroozfard & Kuan Yew Wong & Adnan Hassan, 2016. "A Hybrid Genetic Algorithm with a Knowledge-Based Operator for Solving the Job Shop Scheduling Problems," Journal of Optimization, Hindawi, vol. 2016, pages 1-13, April.
    6. Sels, Veronique & Craeymeersch, Kjeld & Vanhoucke, Mario, 2011. "A hybrid single and dual population search procedure for the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 215(3), pages 512-523, December.
    7. Ganesan, Viswanath Kumar & Sivakumar, Appa Iyer, 2006. "Scheduling in static jobshops for minimizing mean flowtime subject to minimum total deviation of job completion times," International Journal of Production Economics, Elsevier, vol. 103(2), pages 633-647, October.
    8. Fowler, John W. & Mönch, Lars, 2022. "A survey of scheduling with parallel batch (p-batch) processing," European Journal of Operational Research, Elsevier, vol. 298(1), pages 1-24.
    9. Ramalhinho Lourenco, Helena, 1996. "Sevast'yanov's algorithm for the flow-shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 91(1), pages 176-189, May.
    10. Taudes, Alfred & Trcka, Michael & Lukanowicz, Martin, 2002. "Organizational learning in production networks," Journal of Economic Behavior & Organization, Elsevier, vol. 47(2), pages 141-163, February.
    11. D J Stewardson & R I Whitfield, 2004. "A demonstration of the utility of fractional experimental design for finding optimal genetic algorithm parameter settings," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(2), pages 132-138, February.
    12. Liaw, Ching-Fang, 2000. "A hybrid genetic algorithm for the open shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 124(1), pages 28-42, July.
    13. Rego, César & Duarte, Renato, 2009. "A filter-and-fan approach to the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 194(3), pages 650-662, May.
    14. Bürgy, Reinhard & Bülbül, Kerem, 2018. "The job shop scheduling problem with convex costs," European Journal of Operational Research, Elsevier, vol. 268(1), pages 82-100.
    15. Zoghby, Jeriad & Wesley Barnes, J. & Hasenbein, John J., 2005. "Modeling the reentrant job shop scheduling problem with setups for metaheuristic searches," European Journal of Operational Research, Elsevier, vol. 167(2), pages 336-348, December.
    16. Sabuncuoglu, I. & Bayiz, M., 1999. "Job shop scheduling with beam search," European Journal of Operational Research, Elsevier, vol. 118(2), pages 390-412, October.
    17. Ronconi, Débora P. & Henriques, Luís R.S., 2009. "Some heuristic algorithms for total tardiness minimization in a flowshop with blocking," Omega, Elsevier, vol. 37(2), pages 272-281, April.
    18. Andrzej Jaszkiewicz & Thibaut Lust, 2017. "Proper balance between search towards and along Pareto front: biobjective TSP case study," Annals of Operations Research, Springer, vol. 254(1), pages 111-130, July.
    19. Mukherjee, Saral & Chatterjee Ashis K, 2002. "Applying Machine Based Decomposition in 2-Machine Flow Shops," IIMA Working Papers WP2002-08-05, Indian Institute of Management Ahmedabad, Research and Publication Department.
    20. Guinet, Alain & Legrand, Marie, 1998. "Reduction of job-shop problems to flow-shop problems with precedence constraints," European Journal of Operational Research, Elsevier, vol. 109(1), pages 96-110, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:181:y:2010:i:1:p:745-765:10.1007/s10479-010-0751-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.