简介：Tubinecascadeoptimumdesign,thetypicalnon-convexoptimalproblem,haslongbeenadesignchallengeintheengineeringfields.ThenewtypehybridGeneticAlgorithms-wholeannealingGeneticAlgorithmshavebeendevelopedinthispaper,Simulatedannealingselectionandnon-uniformmutationareadoptedinthewholeannealingGeneticAlgorithms.WholeannealingGeneticAlgorithmsoptimalperformancehavebeentestedthroughmathematicaltestfunctions.Onthisbasis,turbinecascadeinversedesignusingwholeannealingGeneticAlgorithmshaebeenpresented.TheB-Splinefunctionisappliedtorepresentthecascadeshape,C-typegridandGodunovschemeareadoptedtoanalysisthecascadeaerodynamicperformance.Theoptimalproblemaimstoobtainancascadeshapefromdifferentinitialcascadethroughthegiventargetpressuredistribution.Theoptimumcascadeshapeisinwellagreementwiththetargetcascadeshape.ThenumericalresultsshowthatthewholeannealingGeneticAlgorithmsarethepowerfuloptimumtoolsforturbineoptimumdesignorothercomplexengineeringdesignproblems.

简介：Inrecentyears,heavyionbeamshavebeenrecognizedasaneffectiveandefficientphysicalmutagenduetotheircapacitytoinducemutationswithhighfrequencyandbroadspectrum.Nowadays,itisnotsodifficulttoproducevariousmutantsinplants.However,tominetheresponsiblemutatedgeneshasbeenanimportantchallenge.Formutationisolation,map-basedcloningisoneofthemajortraditionalwaystoisolatethemutantgenesthatcontroltraitsofinterestinforwardgeneticsstudies.However,theprocessofmap-basedcloningisusuallycomplicatedandtime-consuming.