IDEAS home Printed from https://ideas.repec.org/a/hin/complx/8903005.html
   My bibliography  Save this article

Chaotic Honeybees Optimization Algorithms Approach for Traveling Salesperson Problem

Author

Listed:
  • Pedro Palominos
  • Carla Ortega
  • Miguel Alfaro
  • Guillermo Fuertes
  • Manuel Vargas
  • Mauricio Camargo
  • Victor Parada
  • Gustavo Gatica
  • Jesus M. Munoz-Pacheco

Abstract

Due to the difficulty in solving combinatorial optimization problems, it is necessary to improve the performance of the algorithms by improving techniques to deal with complex optimizations. This research addresses the metaheuristics of marriage in honey-bees optimization (MBO) based on the behavior of bees. The current study proposes a technique for solving combinatorial optimization problems within proper computation times. The purpose of this study focuses on the travelling salesperson problem and the application of chaotic methods in important sections of the MBO metaheuristic. Three experiments were conducted to measure the efficiency and quality of the solutions: (1) MBO with chaos to generate initial solutions (MBO2); (2) MBO with chaos in the workers (MBO3); and (3) MBO with chaos to generate initial solutions and the workers (MBO4). The application of chaotic functions in MBO was significantly better at solving the travelling salesperson problem.

Suggested Citation

  • Pedro Palominos & Carla Ortega & Miguel Alfaro & Guillermo Fuertes & Manuel Vargas & Mauricio Camargo & Victor Parada & Gustavo Gatica & Jesus M. Munoz-Pacheco, 2022. "Chaotic Honeybees Optimization Algorithms Approach for Traveling Salesperson Problem," Complexity, Hindawi, vol. 2022, pages 1-17, October.
    • Handle: RePEc:hin:complx:8903005
    DOI: 10.1155/2022/8903005
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/complexity/2022/8903005.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/complexity/2022/8903005.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2022/8903005?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
    ---><---

    Citations

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


    Cited by:

    1. Pedro Palominos & Mauricio Mazo & Guillermo Fuertes & Miguel Alfaro, 2025. "An Improved Marriage in Honey-Bee Optimization Algorithm for Minimizing Earliness/Tardiness Penalties in Single-Machine Scheduling with a Restrictive Common Due Date," Mathematics, MDPI, vol. 13(3), pages 1-29, January.

    More about this item

    Statistics

    Access and download statistics

    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:hin:complx:8903005. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.