IDEAS home Printed from https://ideas.repec.org/a/spr/opsear/v61y2024i3d10.1007_s12597-024-00746-4.html
   My bibliography  Save this article

Optimizing hyperparameters in Hopfield neural networks using evolutionary search

Author

Listed:
  • Safae Rbihou

    (Sidi Mohamed Ben Abdellah University)

  • Khalid Haddouch

    (Sidi Mohamed Ben Abdellah University)

  • Karim El moutaouakil

    (Sidi Mohamed Ben Abdellah University of Fez)

Abstract

The major problem facing users of Hopfield neural networks is the automatic choice of hyperparameters depending on the optimisation problem. This work introduces an automatic method to overcome this problem based on an original mathematical model minimizing the energy function. This methods ensures the feasibility of optimal solution obtained by decomposing the set of the feasible solutions. We illustrate the proposed model in the context of six well-known NP-hard problems: meeting scheduling problem, Kohonen network problem, portfolio selection problem, traveling salesman problem, task assignment problem, and max-stable problem. To show the effectiveness of our model, we use particle swarm and genetic algorithms to solve several instances of the last three problems. Numerical results show the good performance of the proposed approach compared to random tuning hyperparameters methods. Indeed, our approach permits an improvement of 49.75% for traveling salesman problem, 5.92% for task assignment problem, and 29.41% for max-stable problem.

Suggested Citation

  • Safae Rbihou & Khalid Haddouch & Karim El moutaouakil, 2024. "Optimizing hyperparameters in Hopfield neural networks using evolutionary search," OPSEARCH, Springer;Operational Research Society of India, vol. 61(3), pages 1245-1273, September.
    • Handle: RePEc:spr:opsear:v:61:y:2024:i:3:d:10.1007_s12597-024-00746-4
    DOI: 10.1007/s12597-024-00746-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12597-024-00746-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12597-024-00746-4?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. Karim El Moutaouakil & Abdellatif El Ouissari & Adrian Olaru & Vasile Palade & Mihaela Ciorei, 2023. "OPT-RNN-DBSVM: OPTimal Recurrent Neural Network and Density-Based Support Vector Machine," Mathematics, MDPI, vol. 11(16), pages 1-28, August.
    2. Satake, Tsuyoshi & Morikawa, Katsumi & Nakamura, Nobuto, 1994. "Neural network approach for minimizing the makespan of the general job-shop," International Journal of Production Economics, Elsevier, vol. 33(1-3), pages 67-74, January.
    3. Gerhard Reinelt, 1991. "TSPLIB—A Traveling Salesman Problem Library," INFORMS Journal on Computing, INFORMS, vol. 3(4), pages 376-384, November.
    4. Prashant Singh & Ankush R. Kamthane & Ajinkya N. Tanksale, 2021. "Metaheuristics for the distance constrained generalized covering traveling salesman problem," OPSEARCH, Springer;Operational Research Society of India, vol. 58(3), pages 575-609, September.
    5. Lu, Peng & Ye, Lin & Zhao, Yongning & Dai, Binhua & Pei, Ming & Tang, Yong, 2021. "Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges," Applied Energy, Elsevier, vol. 301(C).
    6. Ekta Jain & Kalpana Dahiya & Vanita Verma, 2020. "A priority based unbalanced time minimization assignment problem," OPSEARCH, Springer;Operational Research Society of India, vol. 57(1), pages 13-45, March.
    7. Kate A. Smith, 1999. "Neural Networks for Combinatorial Optimization: A Review of More Than a Decade of Research," INFORMS Journal on Computing, INFORMS, vol. 11(1), pages 15-34, February.
    8. Karim El Moutaouakil & Abdellatif El Ouissari & Vasile Palade & Anas Charroud & Adrian Olaru & Hicham Baïzri & Saliha Chellak & Mouna Cheggour, 2023. "Multi-Objective Optimization for Controlling the Dynamics of the Diabetic Population," Mathematics, MDPI, vol. 11(13), pages 1-28, July.
    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. William Cook & Sanjeeb Dash & Ricardo Fukasawa & Marcos Goycoolea, 2009. "Numerically Safe Gomory Mixed-Integer Cuts," INFORMS Journal on Computing, INFORMS, vol. 21(4), pages 641-649, November.
    2. Thiago Serra & Ryan J. O’Neil, 2020. "MIPLIBing: Seamless Benchmarking of Mathematical Optimization Problems and Metadata Extensions," SN Operations Research Forum, Springer, vol. 1(3), pages 1-6, September.
    3. Barbato, Michele & Gouveia, Luís, 2024. "The Hamiltonian p-median problem: Polyhedral results and branch-and-cut algorithms," European Journal of Operational Research, Elsevier, vol. 316(2), pages 473-487.
    4. S Salhi & A Al-Khedhairi, 2010. "Integrating heuristic information into exact methods: The case of the vertex p-centre problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(11), pages 1619-1631, November.
    5. Marilène Cherkesly & Claudio Contardo, 2021. "The conditional p-dispersion problem," Journal of Global Optimization, Springer, vol. 81(1), pages 23-83, September.
    6. Malaguti, Enrico & Martello, Silvano & Santini, Alberto, 2018. "The traveling salesman problem with pickups, deliveries, and draft limits," Omega, Elsevier, vol. 74(C), pages 50-58.
    7. Bernardino, Raquel & Paias, Ana, 2018. "Solving the family traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 267(2), pages 453-466.
    8. Ernst Althaus & Felix Rauterberg & Sarah Ziegler, 2020. "Computing Euclidean Steiner trees over segments," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 8(3), pages 309-325, October.
    9. Rafael Blanquero & Emilio Carrizosa & Amaya Nogales-Gómez & Frank Plastria, 2014. "Single-facility huff location problems on networks," Annals of Operations Research, Springer, vol. 222(1), pages 175-195, November.
    10. Martins, Francisco Leonardo Bezerra & do Nascimento, José Cláudio, 2022. "Power law dynamics in genealogical graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    11. Marjan Marzban & Qian-Ping Gu & Xiaohua Jia, 2016. "New analysis and computational study for the planar connected dominating set problem," Journal of Combinatorial Optimization, Springer, vol. 32(1), pages 198-225, July.
    12. Ferrer, José M. & Martín-Campo, F. Javier & Ortuño, M. Teresa & Pedraza-Martínez, Alfonso J. & Tirado, Gregorio & Vitoriano, Begoña, 2018. "Multi-criteria optimization for last mile distribution of disaster relief aid: Test cases and applications," European Journal of Operational Research, Elsevier, vol. 269(2), pages 501-515.
    13. R. Baldacci & E. Hadjiconstantinou & A. Mingozzi, 2004. "An Exact Algorithm for the Capacitated Vehicle Routing Problem Based on a Two-Commodity Network Flow Formulation," Operations Research, INFORMS, vol. 52(5), pages 723-738, October.
    14. Roberto Tadei & Guido Perboli & Francesca Perfetti, 2017. "The multi-path Traveling Salesman Problem with stochastic travel costs," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 3-23, March.
    15. Jesus Garcia-Diaz & Jairo Sanchez-Hernandez & Ricardo Menchaca-Mendez & Rolando Menchaca-Mendez, 2017. "When a worse approximation factor gives better performance: a 3-approximation algorithm for the vertex k-center problem," Journal of Heuristics, Springer, vol. 23(5), pages 349-366, October.
    16. Thomas R. Visser & Remy Spliet, 2020. "Efficient Move Evaluations for Time-Dependent Vehicle Routing Problems," Transportation Science, INFORMS, vol. 54(4), pages 1091-1112, July.
    17. Fatih Rahim & Canan Sepil, 2014. "A location-routing problem in glass recycling," Annals of Operations Research, Springer, vol. 223(1), pages 329-353, December.
    18. F J Vasko & J D Bobeck & M A Governale & D J Rieksts & J D Keffer, 2011. "A statistical analysis of parameter values for the rank-based ant colony optimization algorithm for the traveling salesperson problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1169-1176, June.
    19. Francesco Carrabs & Jean-François Cordeau & Gilbert Laporte, 2007. "Variable Neighborhood Search for the Pickup and Delivery Traveling Salesman Problem with LIFO Loading," INFORMS Journal on Computing, INFORMS, vol. 19(4), pages 618-632, November.
    20. J Renaud & F F Boctor & G Laporte, 2004. "Efficient heuristics for Median Cycle Problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(2), pages 179-186, February.

    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:opsear:v:61:y:2024:i:3:d:10.1007_s12597-024-00746-4. 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.