• DocumentCode
    1637755
  • Title

    Mixed Mutation Strategy Embedded Differential Evolution

  • Author

    Pant, Millie ; Ali, Musrrat ; Abraham, Ajith

  • Author_Institution
    Indian Inst. of Technol. Roorkee, Saharanpur
  • fYear
    2009
  • Firstpage
    1240
  • Lastpage
    1246
  • Abstract
    Differential evolution (DE) is a powerful yet simple evolutionary algorithm for optimizing real valued optimization problems. Traditional investigations with differential evolution have used a single mutation operator. Using a variety of mutation operators that can be integrated during evolution could hold the potential to generate a better solution with less computational effort. In view of this, in this paper a mixed mutation strategy which uses the concept of evolutionary game theory is proposed to integrate basic differential evolution mutation and quadratic interpolation to generate a new solution. Throughout of this paper we refer this new algorithm as, differential evolution with mixed mutation strategy (MSDE). The performance of proposed algorithm is investigated and compared with basic differential evolution. The experiments conducted shows that proposed algorithm outperform the basic DE algorithm in all the benchmark problems.
  • Keywords
    evolutionary computation; game theory; interpolation; optimisation; DE; differential evolution; evolutionary algorithm; game theory; mixed mutation strategy; quadratic interpolation; real valued optimization problem; Convergence; Evolutionary computation; Game theory; Genetic algorithms; Genetic mutations; Genetic programming; Interpolation; Machine intelligence; Quality of service; differential evolution; mixed strategy; mutation operator;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2009. CEC '09. IEEE Congress on
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-2958-5
  • Electronic_ISBN
    978-1-4244-2959-2
  • Type

    conf

  • DOI
    10.1109/CEC.2009.4983087
  • Filename
    4983087