• Title of article

    A novelcompetitiveco-evolutionaryquantumgeneticalgorithmforstochasticjob shop schedulingproblem

  • Author/Authors

    Jinwei Gu، نويسنده , , ManzhanGub، نويسنده , , CuiwenCao، نويسنده , , XingshengGu، نويسنده ,

  • Issue Information
    ماهنامه با شماره پیاپی سال 2010
  • Pages
    11
  • From page
    927
  • To page
    937
  • Abstract
    In thispaper,anovelcompetitiveco-evolutionaryquantumgeneticalgorithm(CCQGA)isproposedfor a stochasticjobshopschedulingproblem(SJSSP)withtheobjectivetominimizetheexpectedvalueof makespan. Threenewstrategiesnamedascompetitivehunter,cooperativesurvivingandthebigfish eating smallfisharedevelopedinpopulationgrowthprocess.Basedonimprovedco-evolutionideaof multi-population andconceptsofquantumtheory,thisalgorithmcouldnotonlyadjustpopulationsize dynamically toincreasethediversityofgenesandavoidprematureconvergence,butalsoacceleratethe convergence speedwithQ-bitrepresentationandquantumrotationgate.FTbenchmark-basedproblems where theprocessingtimesaresubjectedtoindependentnormaldistributionsaresolvedeffectively by CCQGA.TheexperimentresultsachievedbyCCQGAarecomparedwithquantum-inspiredgenetic algorithm (QGA)andstandardgeneticalgorithm(GA),whichshowsthatCCQGAhasbetterfeasibilityand effectiveness.
  • Keywords
    Stochastic , Job shop scheduling , Competitive , Co-evolution algorithm , Genetic Algorithm
  • Journal title
    Computers and Operations Research
  • Serial Year
    2010
  • Journal title
    Computers and Operations Research
  • Record number

    927702

    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=10&DC=927702