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1、1286IEEETRANSACTIONSONANTENNASANDPROPAGATION,VOL.59,NO.4,APRIL2011Self-AdaptiveDifferentialEvolutionAppliedtoReal-ValuedAntennaandMicrowaveDesignProblemsSotiriosK.Goudos,Member,IEEE,KatherineSiakavara,Member,IEEE,TheodorosSamaras,Member,IEEE,EliasE.Va?adis,Member,IEEE,andJohnN.Sahalos,Li
2、feFellow,IEEEAbstract—Particleswarmoptimization(PSO)isanevolutionarybeenappliedtomicrowavestructures[26]–[28],antennadesignalgorithmbasedonthebird?y.Differentialevolution(DE)isa[29]–[35],signaloptimization[36]andmicrowaveimagingap-vectorpopulationbasedstochasticoptimizationmethod.Thefact
3、plications[37]–[44].thatbothalgorithmscanhandleef?cientlyarbitraryoptimizationDEproducedbetterresultsthanPSOonnumericalbench-problemshasmadethempopularforsolvingproblemsinelectro-magnetics.Inthispaper,weapplyadesigntechniquebasedonamarkproblemswithlowandmediumdimensionality(30andself-ada
4、ptiveDE(SADE)algorithmtoreal-valuedantennaand100dimensions)[45].However,onnoisytestproblems,DEwasmicrowavedesignproblems.Theseincludelinear-arraysynthesis,outperformedbyPSO.In[46]acomparativestudybetweenDEpatch-antennadesignandmicrostrip?lterdesign.ThenumberandPSOvariantsispresentedforth
5、edesignofradarabsorbingofunknownsforthedesignproblemsvariesfrom6to60.Wecomparetheself-adaptiveDEstrategywithpopularPSOandmaterials(RAM).Thenumberofproblemdimensionswas10DEvariants.Weevaluatethealgorithms’performanceregardingandDEoutperformedthePSOvariantsintermsofconvergencestatisticalre
6、sultsandconvergencespeed.Theresultsobtainedforspeedandbestvaluesfound.Theshapereconstructionofaper-differentproblemsshowthattheDEalgorithmsoutperformthefectlyconducting2-DscattererusingDEandPSOispresentedPSOvariantsintermsof?ndingbestoptima.Thus,ourresultsin[40],[44].Alsobothalgorithmsha
7、vebeenappliedto1-DshowtheadvantagesoftheSADEstrategyandtheDEingeneral.However,theseresultsareconsideredtobeindicativeanddonotsmall-scaleinversescatteringproblems[43].Inthesecases,DEgenerallyapplytoalloptimizationproblemsinelectromagnetics.outperformedPSO.In[47]acomparison
