• DocumentCode
    1867680
  • Title

    Biased random key genetic algorithm with hybrid decoding for multi-objective optimization

  • Author

    Tangpattanakul, Panwadee ; Jozefowiez, Nicolas ; Lopez, Pierre

  • Author_Institution
    LAAS, Univ. de Toulouse, Toulouse, France
  • fYear
    2013
  • fDate
    8-11 Sept. 2013
  • Firstpage
    393
  • Lastpage
    400
  • Abstract
    A biased random key genetic algorithm (BRKGA) is an efficient method for solving combinatorial optimization problems. It can be applied to solve both single-objective and multi-objective optimization problems. The BRKGA operates on a chromosome encoded as a key vector of real values between [0, 1]. Generally, the chromosome has to be decoded by using a single decoding method in order to obtain a feasible solution. This paper presents a hybrid decoding, which combines the operation of two single decoding methods. This hybrid decoding gives two feasible solutions from the decoding of one chromosome. Experiments are conducted on realistic instances, which concern acquisition scheduling of agile Earth observing satellites.
  • Keywords
    combinatorial mathematics; genetic algorithms; BRKGA; acquisition scheduling; agile Earth observing satellites; biased random key genetic algorithm; combinatorial optimization problems; hybrid decoding; hybrid decoding method; multiobjective optimization; multiobjective optimization problems; single decoding method; single-objective optimization problems; Biological cells; Decoding; Genetic algorithms; Optimization; Satellites; Sociology; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on
  • Conference_Location
    Krako??w
  • Type

    conf

  • Filename
    6644030