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一种基于Lévy飞行的细菌觅食优化算法.docx

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一种基于Lévy飞行的细菌觅食优化算法 Abstract Bacterialforagingoptimization(BFO)algorithmisapopularoptimizationalgorithminspiredbythebehaviorofbacterialforaging.However,therearesomechallengesintheBFOalgorithm,includingtheslowconvergencespeedandthelowsearchingaccuracy.Toovercomethesechallenges,thispaperproposesanovelBFOalgorithmbasedonLévyflight.TheproposedalgorithmintroducesLévyflightbehaviorintotheforagingprocesstoimprovetheexplorationcapabilityandthelocalsearchprecision.ExperimentalresultsshowthattheproposedalgorithmcanimprovetheperformanceoftheBFOalgorithmintermsofconvergencespeed,searchaccuracyandrobustness. Introduction Thebacterialforagingoptimization(BFO)algorithmisaheuristicsearchalgorithminspiredbythebehaviorofbacterialforaging.TheBFOalgorithmmimicsthechemotaxis,reproduction,andeliminationprocessesinthebacterialforagingbehaviortosearchfortheoptimalsolutioninagivenoptimizationproblem.Despiteitsgoodperformance,theBFOalgorithmstillfacessomechallengessuchasslowconvergencespeedandlowsearchingaccuracy.Toovercomethesechallenges,thispaperproposesanovelBFOalgorithmbasedonLévyflight. Lévyflightisapower-lawrandomwalk,whichhasbeenwidelyusedinmanyfields,suchasphysics,biology,andfinance.TheLévyflightcanbeusedtomodeltheforagingbehaviorofsomeanimalssuchasbeesandbirds.Inrecentyears,theLévyflighthasbeenintroducedintotheoptimizationalgorithmstoimprovetheirexplorationcapabilityandlocalsearchprecision. Inthispaper,weproposeaBFOalgorithmbasedonLévyflighttoimprovethesearchperformanceoftheBFO.Intheproposedalgorithm,weintroducetheLévyflightbehaviorintotheforagingprocessofthebacteria.TheLévyflightbehaviorcanincreasetheexplorationcapabilityofthebacteriaandpreventprematureconvergence.Theproposedalgorithmisimplementedandtestedonseveraloptimizationproblems.ExperimentalresultsshowthattheproposedalgorithmoutperformsthetraditionalBFOalgorithmintermsofconvergencespeed,searchaccuracy,androbustness. Theremainderofthispaperisorganizedasfollows:Section2providesabriefoverviewoftheBFOalgorithmandLévyflight.Sectio