• DocumentCode
    1580624
  • Title

    Symbiotic Tabu Search, A General Evolutionary Optimization Approach

  • Author

    Halavati, Ramin ; Shouraki, Saeed Bagheri ; Jashmi, Bahareh Jafari ; Heravi, Mojdeh Jalali

  • Author_Institution
    Sharif Univ. of Technol., Tehran
  • fYear
    2007
  • Firstpage
    138
  • Lastpage
    143
  • Abstract
    Recombination in the Genetic Algorithm (GA) is supposed to extract the component characteristics from two parents and reassemble them in different combinations - hopefully producing an offspring that has the good characteristics of both parents. Symbiotic Combination is formerly introduced as an alternative for sexual recombination operator to overcome the need of explicit design of recombination operators in GA. This paper presents an optimization algorithm based on using this operator in Tabu Search. The algorithm is benchmarked on two problem sets and is compared with standard genetic algorithm and symbiotic evolutionary adaptation model, showing success rates higher than both cited algorithms.
  • Keywords
    genetic algorithms; search problems; evolutionary optimization approach; genetic algorithm; recombination operators; sexual recombination operator; symbiotic Tabu Search; symbiotic combination; symbiotic evolutionary adaptation model; Adaptation model; Bioinformatics; Biological cells; Couplings; Genetic algorithms; Genetic engineering; Genomics; Hybrid intelligent systems; Organisms; Symbiosis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Hybrid Intelligent Systems, 2007. HIS 2007. 7th International Conference on
  • Conference_Location
    Kaiserlautern
  • Print_ISBN
    978-0-7695-2946-2
  • Type

    conf

  • DOI
    10.1109/HIS.2007.70
  • Filename
    4344041