• DocumentCode
    1794723
  • Title

    Multi-Genomic Algorithms

  • Author

    Ngo, Mathias ; Labayrade, Raphael

  • Author_Institution
    Univ. de Lyon, Lyon, France
  • fYear
    2014
  • fDate
    9-12 Dec. 2014
  • Firstpage
    48
  • Lastpage
    55
  • Abstract
    The first step of any optimization process consists in choosing the Decision Variables (DV) and its relationships that model the problem, system or object to optimize. Many problems cannot be represented by a unique, exhaustive model which would ensure a global best result: in those cases, the model (DV and relationships) choice matters on the quality of the results.
  • Keywords
    biology computing; cellular biophysics; decision making; genetic algorithms; genomics; 2D shape optimization; DV; GA; MGA; chromosomes; decision variables; exhaustive model; genetic algorithms; multigenomic algorithms; multigenomic populations; optimization process; unique genome; Bioinformatics; Biological cells; Computational modeling; Genomics; Optimization; Sociology; Statistics; Computational Speed Improvement; Evolutionary Algorithms; Genetic Algorithms; Model Reduction; Model Refinement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Multi-Criteria Decision-Making (MCDM), 2014 IEEE Symposium on
  • Conference_Location
    Orlando, FL
  • Type

    conf

  • DOI
    10.1109/MCDM.2014.7007187
  • Filename
    7007187