• DocumentCode
    506624
  • Title

    An improved niche genetic algorithm

  • Author

    Ming, Huang ; Nan, Liu ; Xu, Liang

  • Author_Institution
    Software Technol. Inst., Dalian Jiao Tong Univ. Dalian, Dalian, China
  • Volume
    2
  • fYear
    2009
  • fDate
    20-22 Nov. 2009
  • Firstpage
    291
  • Lastpage
    293
  • Abstract
    Based on the genetic algorithm for solving multi-objective optimization easily leads to the defect of premature and slow convergence, so an improved niche genetic algorithm is proposed. This algorithm is to select distance parameter equals to the minimum Euclidean distance between the best individuals, using the method of allele comparison to determine within the distance parameter individuals whether similar. Using this method solves the problem of multi-objective optimization, which can produce a better niche environment, greatly protect the diversity of population and improve the search efficiency. The simulation results show that new algorithm effectively avoids falling into local optimal solutions, and performance is superior to the existing algorithms.
  • Keywords
    genetic algorithms; minimum Euclidean distance; multiobjective optimization; niche genetic algorithm; Biological cells; Electronic mail; Euclidean distance; Genetic algorithms; Job shop scheduling; Optimal control; Optimization methods; Protection; Scheduling algorithm; Software maintenance; distance parameter; multi-objective; niche genetic algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-4754-1
  • Electronic_ISBN
    978-1-4244-4738-1
  • Type

    conf

  • DOI
    10.1109/ICICISYS.2009.5357965
  • Filename
    5357965