蚁群算法及其应用研究(3)

发布时间:2021-06-06

●___Il●●●l,I—_●I——I——_ lII _l_l●__●IlIl___l _I Abstract

Abstract

Biologists’studyfoundthatnatural

pheromoneantscouldreleaseachemicalsubstanceknownascommunicationandthroughwhich

aantcolonyconductindirectcooperationinordertofindshortestpathfromnesttofood.Inspiredbytheant’s

behavior,ItalyscholarDorigoandhiscolleaguesdidsomesimulationresearchbycomputer.Forthefirsttime,theyproposed

years,antantcolonyalgorithm.Inthefollowing10colonyalgorithmwasappliedtoCombinatorialoptimization,network

SOrouting,functionoptimization,datamining,robotpathplanningand

showsthegreaton,whichadvantageofantcolonyalgorithminsolvingcomplexproblemsandabrightfutureforfurtherdevelopment.

However,therearestillsomedefectsinantcolonyalgorithmsuchascostingtoomuchtimeandeasytodropintostagnation.Thispaperfocusesontheprincipleofantcolonyoptimizationandits

antcolonyapplication.WeasdosomeresearchonimprovementuponalgorithmaswellapplicationtoTSP(TravelingSalesmanProblem)and

onMKP(Multidimensional

andKnapsackProblem).Basedaccuracyofstandarddatasetswecomparealgorithmsanalyzetheefficiencyandoriginalandproposedalgorithms.

First,anewAntColonyOptimizationalgorithmbased

diffusionmodelisproposed.It

energyconversationandonpheromoneincrementandadoptsanewpheromoneupdatemechanismbasedontransformwhichintegrates

pheromonetheimpactofglobalinformationandlocalinformationonandembodiesthepheromonedifferencefor

originalpheromonediffusionmodeland

tofaithfullyreflectadifferentpaths.Meanwhile,weimprovethepathpheromonediffusionmodelisestablishedthestrengthfieldof

pheromonediffusionwhichstrengthensthecollaborationamongants.Amutationstrategy、^,itll

result.lowercomputationalcomplexityisadoptedtooptimizeeachevolution

Second,aimingatsolvinglarge—scaleTravelingSalesmanProblemswhichconsume

alargecomputation,anewalgorithmisproposed.Itadopts

strategiestolookforansetareofmultistageoptimalsolution.Firstly,thecitiesofTSPclusteredintoseveraldistrictsbymeansofdensity-basedalgorithm.Secondly,theantalgorithm

tosolving

abasedonpheromonediffusionmodelisappliedinparallelizationthesub—problemineachdistrict.Then,alldistrictsolutionsareintegratedintosolution.

Finally,localoptimizationisconductedbymeansofPartitionoptimization.Onthis

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