• DocumentCode
    2166874
  • Title

    Multiobjective evolutionary algorithm MOEA to solve task allocation problems in multi agents systems

  • Author

    Mauledoux, Mauricio ; Shkodyrev, Viacheslav

  • Author_Institution
    Distrib. Intell. Syst. Dept., State Polytech. Univ., St. Petersburg, Russia
  • Volume
    5
  • fYear
    2010
  • fDate
    26-28 Feb. 2010
  • Firstpage
    839
  • Lastpage
    842
  • Abstract
    The work is devoted to solve allocation task problem in the distributed way in multi agents systems with multi-objective genetic algorithms. The paper shows the main advantages of genetic algorithms and the way to apply a new genetic operator using the solution information of the other agents for save time in the search a expand the solution of the optimal space.
  • Keywords
    genetic algorithms; multi-agent systems; task analysis; MOEA; multi agents systems; multiobjective evolutionary algorithm; multiobjective genetic algorithms; task allocation; Aggregates; Artificial intelligence; Decision making; Evolutionary computation; Genetic algorithms; Intelligent agent; Intelligent systems; Pareto optimization; Uncertainty; Genetic algorithms; Multi agent system; component; multi-objective optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-5585-0
  • Electronic_ISBN
    978-1-4244-5586-7
  • Type

    conf

  • DOI
    10.1109/ICCAE.2010.5451885
  • Filename
    5451885