IDEAS home Printed from https://ideas.repec.org/a/hin/jnlaor/956498.html
   My bibliography  Save this article

A Genetic Algorithm with Fuzzy Crossover Operator and Probability

Author

Listed:
  • Mohammad Jalali Varnamkhasti
  • Lai Soon Lee
  • Mohd Rizam Abu Bakar
  • Wah June Leong

Abstract

The performance of a genetic algorithm is dependent on the genetic operators, in general, and on the type of crossover operator, in particular. The population diversity is usually used as the performance measure for the premature convergence. In this paper, a fuzzy genetic algorithm is proposed for solving binary encoded combinatorial optimization problems. A new crossover operator and probability selection technique is proposed based on the population diversity using a fuzzy logic controller. The measurement of the population diversity is based on the genotype and phenotype properties. In this fuzzy inference system, the selection of the crossover operator and its probability are controlled by a set of fuzzy rules derived from the fuzzy logic controller. Extensive computational experiments are conducted on the proposed algorithm, and the results are compared with some crossover operators commonly used for solving multidimensional 0/1 knapsack problems published in the literature. The results indicate that the proposed algorithm is effective in finding better quality solutions.

Suggested Citation

  • Mohammad Jalali Varnamkhasti & Lai Soon Lee & Mohd Rizam Abu Bakar & Wah June Leong, 2012. "A Genetic Algorithm with Fuzzy Crossover Operator and Probability," Advances in Operations Research, Hindawi, vol. 2012, pages 1-16, February.
  • Handle: RePEc:hin:jnlaor:956498
    DOI: 10.1155/2012/956498
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/AOR/2012/956498.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/AOR/2012/956498.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2012/956498?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. Ertunç, Ela & Çay, Tayfun & Haklı, Hüseyin, 2018. "Modeling of reallocation in land consolidation with a hybrid method," Land Use Policy, Elsevier, vol. 76(C), pages 754-761.
    2. Stock-Williams, Clym & Swamy, Siddharth Krishna, 2019. "Automated daily maintenance planning for offshore wind farms," Renewable Energy, Elsevier, vol. 133(C), pages 1393-1403.

    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:jnlaor:956498. 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.