欢迎来到天天文库
浏览记录
ID:36636225
大小:1.18 MB
页数:54页
时间:2019-05-13
《蚁群算法的改进及其在车辆路径问题中的应用》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、西南交通大学硕士学位论文蚁群算法的改进及其在车辆路径问题中的应用姓名:郭倩倩申请学位级别:硕士专业:应用数学指导教师:黄天民20070401西南交通大学硕士研究生学位论文第ll页AbstractOptimizationtechnologyisatechnologybasedonmathematicsandappliedtoallkindsofoptimizationsolutiontoengineeringproblems.Asanimportantbranchofscience,itisalway
2、sattachedwideimportancetoandrapidlyextendedandappliedtoindustryandeconomy,andsoon.Becauseofcomplication,large—scale,non—Iinearanddifficultiesofmodelinginengineeringoptimization,ithasbeenamainresearchobjectanddirectionthatfindsanintelligentandgeneral—pu
3、rposeglobaloptimizationmethodforlarge—scaleparallelization.Since1980s,somenovelheuristicsalgorithmsarecreatedbysimulatingorshowingsomenaturalphenomena,suchasGeneticAlgorithms,SimulatedAnnealing,TabooSearch,AntColonyOptimization.Theparticularadvantagean
4、dmechanismofthesealgorithmshavebroughtahot—spotofresearch,especiallyAntColonyOptimizationhasbeendevelopedformorethantenyears.Apopulation—basedsimulatedevolutionaryalgorithmcalledantcolonyoptimization(ACOforshort)wasproposedbyItalianM.Dorigo.ACOadoptspa
5、rallelcomputationmechanism,hasstrongrobustnessandiseasytocombine可ithothermethodsinoptimization.Becauseofitscharacteristics,theresearchoftheoryandapplicationofACOhasgreatmerit.Firstly,thispaperanalyzesthebasictheoryandmodelofACO,introducesthefeaturesofA
6、COandselectssomekeyparameters’valueofACObyexperiments.Secondly,theslowconvergenceandstagnationbehavior。soanimprovedalgorithmisproposed.Thisalgorithmisabletorestrainstagnationduringtheiterationprocesseffectively,and西南交通大学硕士研究生学位论文第llI页enhancethecapabili
7、tyofsearch.Theimprovedalgorithmisappliedtotravelingsalesmenproblem(TSP).ExperimentalresultsforsolvingTSPareprovedtobeeffective.Finally,theimprovedalgorithmisappliedtovehicleroutingproblem(VRP).SimulationresultsoftheVRPexampledemonstratedtheeffectivenes
8、softhisalgorithm.Keywords:AntColonyOptimization,CombinationalOptimization,TravelingSalesmenProblem,VehicleRoutingProblem西南交通大学硕士研究生学位论文第1页第1章绪论1.1蚁群算法的研究现状受蚁群在觅食过程中总能找到从蚁巢到食物源的最短路径的启发,20世纪90年代初,意大利学者M.Dorigo‘”脚。1等首次提出一种新型的智能优化算法一蚂蚁系统(an
此文档下载收益归作者所有