简介：Therecentlyinventedartificialbeecolony(ABC)algorithmisanoptimizationalgorithmbasedonswarmintelligencethathasbeenusedtosolvemanykindsofnumericalfunctionoptimizationproblems.Itperformswellinmostcases,however,therestillexistsaninsufficiencyintheABCalgorithmthatignoresthefitnessofrelatedpairsofindividualsinthemechanismoffindinganeighboringfoodsource.ThispaperpresentsanimprovedABCalgorithmwithmutuallearning(MutualABC)thatadjuststheproducedcandidatefoodsourcewiththehigherfitnessbetweentwoindividualsselectedbyamutuallearningfactor.TheperformanceoftheimprovedMutualABCalgorithmistestedonasetofbenchmarkfunctionsandcomparedwiththebasicABCalgorithmandsomeclassicalversionsofimprovedABCalgorithms.TheexperimentalresultsshowthattheMutualABCalgorithmwithappropriateparametersoutperformsotherABCalgorithmsinmostexperiments.
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