• DocumentCode
    554605
  • Title

    Research for hybrid genetic algorithms on optimization of cutting linear stock

  • Author

    Guang Dong ; Guang Cai Cui

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Changchun Univ. of Sci. & Technol., Changchun, China
  • Volume
    5
  • fYear
    2011
  • fDate
    12-14 Aug. 2011
  • Firstpage
    2230
  • Lastpage
    2233
  • Abstract
    The improved genetic algorithm i.e. hybrid genetic algorithm is applied to solve problem of cutting linear stock, respective corresponding determination methods and algorithms are given for genetic coding, fitness function, initial population generation and genetic operator. Elitist strategy is used in keeping the excellent individuals of population to make the genetic algorithm more effective.
  • Keywords
    bin packing; genetic algorithms; cutting linear stock; elitist strategy; fitness function; genetic coding; genetic operator; hybrid genetic algorithm; initial population generation; Algorithm design and analysis; Educational institutions; Encoding; Genetic algorithms; Optimization; Raw materials; crossover; genetic code; hybrid genetic algorithms; mutation; optimize cutting stock;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
  • Conference_Location
    Harbin, Heilongjiang, China
  • Print_ISBN
    978-1-61284-087-1
  • Type

    conf

  • DOI
    10.1109/EMEIT.2011.6023554
  • Filename
    6023554
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=554605