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1、BacterialForagingOptimizationAlgorithm:TheoreticalFoundations,Analysis,andApplications1112SwagatamDas,ArijitBiswas,SambartaDasgupta,andAjithAbraham1Dept.ofElectronicsandTelecommunicationEngg,JadavpurUniversity,Kolkata,India2NorwegianUniversityofScienceandTechn
2、ology,Norwayswagatamdas19@yahoo.co.in,arijitbiswas87@gmail.com,sambartadg@gmail.com,ajith.abraham@ieee.orgAbstract.Bacterialforagingoptimizationalgorithm(BFOA)hasbeenwidelyacceptedasaglobaloptimizationalgorithmofcurrentinterestfordistributedoptimizationandcont
3、rol.BFOAisinspiredbythesocialforagingbehaviorofEscherichiacoli.BFOAhasalreadydrawntheattentionofresearchersbecauseofitsefficiencyinsolvingreal-worldoptimizationproblemsarisinginseveralapplicationdomains.TheunderlyingbiologybehindtheforagingstrategyofE.coliisem
4、ulatedinanextraordinarymannerandusedasasimpleoptimizationalgorithm.ThischapterstartswithalucidoutlineoftheclassicalBFOA.ItthenanalysesthedynamicsofthesimulatedchemotaxisstepinBFOAwiththehelpofasimplemathematicalmodel.Takingacuefromtheanalysis,itpresentsanewada
5、ptivevariantofBFOA,wherethechemotacticstepsizeisadjustedontherunaccordingtothecurrentfitnessofavirtualbacterium.Nest,ananalysisofthedynamicsofreproductionoperatorinBFOAisalsodiscussed.ThechapterdiscussesthehybridizationofBFOAwithotheroptimizationtechniquesanda
6、lsoprovidesanaccountofmostofthesignificantapplicationsofBFOAuntildate.1.IntroductionBacteriaForagingOptimizationAlgorithm(BFOA),proposedbyPassino[1],isanewcomertothefamilyofnature-inspiredoptimizationalgorithms.Foroverthelastfivedecades,optimizationalgorithmsl
7、ikeGeneticAlgorithms(GAs)[2],EvolutionaryProgramming(EP)[3],EvolutionaryStrategies(ES)[4],whichdrawtheirinspirationfromevolutionandnaturalgenetics,havebeendominatingtherealmofoptimizationalgorithms.RecentlynaturalswarminspiredalgorithmslikeParticleSwarmOptimiz
8、ation(PSO)[5],AntColonyOptimization(ACO)[6]havefoundtheirwayintothisdomainandprovedtheireffectiveness.Followingthesametrendofswarm-basedalgorithms,PassinoproposedtheBFOAin[1].Appli
