IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v60y2009i2d10.1057_palgrave.jors.2602535.html
   My bibliography  Save this article

A tabu search algorithm for the training of neural networks

Author

Listed:
  • B Dengiz

    (Baskent University)

  • C Alabas-Uslu

    (Maltepe University)

  • O Dengiz

    (Auburn University)

Abstract

The most widely used training algorithm of neural networks (NNs) is back propagation (BP), a gradient-based technique that requires significant computational effort. Metaheuristic search techniques such as genetic algorithms, tabu search (TS) and simulated annealing have been recently used to cope with major shortcomings of BP such as the tendency to converge to a local optimal and a slow convergence rate. In this paper, an efficient TS algorithm employing different strategies to provide a balance between intensification and diversification is proposed for the training of NNs. The proposed algorithm is compared with other metaheuristic techniques found in literature using published test problems, and found to outperform them in the majority of the test cases.

Suggested Citation

  • B Dengiz & C Alabas-Uslu & O Dengiz, 2009. "A tabu search algorithm for the training of neural networks," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(2), pages 282-291, February.
    • Handle: RePEc:pal:jorsoc:v:60:y:2009:i:2:d:10.1057_palgrave.jors.2602535
    DOI: 10.1057/palgrave.jors.2602535
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/palgrave.jors.2602535
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/palgrave.jors.2602535?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. Eglese, R. W., 1990. "Simulated annealing: A tool for operational research," European Journal of Operational Research, Elsevier, vol. 46(3), pages 271-281, June.
    2. Sexton, Randall S. & Dorsey, Robert E. & Johnson, John D., 1999. "Optimization of neural networks: A comparative analysis of the genetic algorithm and simulated annealing," European Journal of Operational Research, Elsevier, vol. 114(3), pages 589-601, May.
    3. Gupta, Jatinder N. D. & Sexton, Randall S., 1999. "Comparing backpropagation with a genetic algorithm for neural network training," Omega, Elsevier, vol. 27(6), pages 679-684, December.
    4. Fred Glover, 1990. "Tabu Search—Part II," INFORMS Journal on Computing, INFORMS, vol. 2(1), pages 4-32, February.
    5. Fred Glover, 1989. "Tabu Search---Part I," INFORMS Journal on Computing, INFORMS, vol. 1(3), pages 190-206, August.
    6. Sexton, Randall S. & Alidaee, Bahram & Dorsey, Robert E. & Johnson, John D., 1998. "Global optimization for artificial neural networks: A tabu search application," European Journal of Operational Research, Elsevier, vol. 106(2-3), pages 570-584, April.
    Full references (including those not matched with items on IDEAS)

    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. Panta Lučić & Dušan Teodorović, 2007. "Metaheuristics approach to the aircrew rostering problem," Annals of Operations Research, Springer, vol. 155(1), pages 311-338, November.
    2. Mohammad Javad Feizollahi & Igor Averbakh, 2014. "The Robust (Minmax Regret) Quadratic Assignment Problem with Interval Flows," INFORMS Journal on Computing, INFORMS, vol. 26(2), pages 321-335, May.
    3. C N Potts & V A Strusevich, 2009. "Fifty years of scheduling: a survey of milestones," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 41-68, May.
    4. Cazzaro, Davide & Fischetti, Martina & Fischetti, Matteo, 2020. "Heuristic algorithms for the Wind Farm Cable Routing problem," Applied Energy, Elsevier, vol. 278(C).
    5. Huang, Yeran & Yang, Lixing & Tang, Tao & Gao, Ziyou & Cao, Fang, 2017. "Joint train scheduling optimization with service quality and energy efficiency in urban rail transit networks," Energy, Elsevier, vol. 138(C), pages 1124-1147.
    6. B Dengiz & C Alabas-Uslu & O Dengiz, 2009. "Optimization of manufacturing systems using a neural network metamodel with a new training approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(9), pages 1191-1197, September.
    7. S-W Lin & K-C Ying, 2008. "A hybrid approach for single-machine tardiness problems with sequence-dependent setup times," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(8), pages 1109-1119, August.
    8. Joseph B. Mazzola & Robert H. Schantz, 1997. "Multiple‐facility loading under capacity‐based economies of scope," Naval Research Logistics (NRL), John Wiley & Sons, vol. 44(3), pages 229-256, April.
    9. Abdmouleh, Zeineb & Gastli, Adel & Ben-Brahim, Lazhar & Haouari, Mohamed & Al-Emadi, Nasser Ahmed, 2017. "Review of optimization techniques applied for the integration of distributed generation from renewable energy sources," Renewable Energy, Elsevier, vol. 113(C), pages 266-280.
    10. Masoud Yaghini & Mohammad Karimi & Mohadeseh Rahbar, 2015. "A set covering approach for multi-depot train driver scheduling," Journal of Combinatorial Optimization, Springer, vol. 29(3), pages 636-654, April.
    11. Chris S. K. Leung & Henry Y. K. Lau, 2018. "Multiobjective Simulation-Based Optimization Based on Artificial Immune Systems for a Distribution Center," Journal of Optimization, Hindawi, vol. 2018, pages 1-15, May.
    12. Ilfat Ghamlouche & Teodor Gabriel Crainic & Michel Gendreau, 2003. "Cycle-Based Neighbourhoods for Fixed-Charge Capacitated Multicommodity Network Design," Operations Research, INFORMS, vol. 51(4), pages 655-667, August.
    13. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    14. Andaryan, Abdullah Zareh & Mousighichi, Kasra & Ghaffarinasab, Nader, 2024. "A heuristic approach to the stochastic capacitated single allocation hub location problem with Bernoulli demands," European Journal of Operational Research, Elsevier, vol. 312(3), pages 954-968.
    15. Haluk Yapicioglu, 2018. "Multiperiod Multi Traveling Salesmen Problem Considering Time Window Constraints with an Application to a Real World Case," Networks and Spatial Economics, Springer, vol. 18(4), pages 773-801, December.
    16. Daniel O’Malley & Velimir V Vesselinov & Boian S Alexandrov & Ludmil B Alexandrov, 2018. "Nonnegative/Binary matrix factorization with a D-Wave quantum annealer," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-12, December.
    17. Marco Antonio Boschetti & Vittorio Maniezzo, 2022. "Matheuristics: using mathematics for heuristic design," 4OR, Springer, vol. 20(2), pages 173-208, June.
    18. C-H Lan & C-C Chen, 2007. "Optimal purchase of two-itemized drugs for a disease," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(3), pages 309-316, March.
    19. G Lulli & U Pietropaoli & N Ricciardi, 2011. "Service network design for freight railway transportation: the Italian case," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2107-2119, December.
    20. Cheung, Kam-Fung & Bell, Michael G.H., 2021. "Improving connectivity of compromised digital networks via algebraic connectivity maximisation," European Journal of Operational Research, Elsevier, vol. 294(1), pages 353-364.

    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:pal:jorsoc:v:60:y:2009:i:2:d:10.1057_palgrave.jors.2602535. 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.palgrave-journals.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.