返回
Optimization of Non-Linear Multiple Traveling Salesman Problem Using K-Means Clustering, Shrink Wrap Algorithm and Meta-Heur

Optimization of Non-Linear Multiple Traveling Salesman Problem Using K-Means Clustering, Shrink Wrap Algorithm and Meta-Heur

ID：39505420

大小：800.93 KB

页数：8页

时间：2019-07-04

Optimization of Non-Linear Multiple Traveling Salesman Problem Using K-Means Clustering, Shrink Wrap Algorithm and Meta-Heur_第1页
Optimization of Non-Linear Multiple Traveling Salesman Problem Using K-Means Clustering, Shrink Wrap Algorithm and Meta-Heur_第2页
Optimization of Non-Linear Multiple Traveling Salesman Problem Using K-Means Clustering, Shrink Wrap Algorithm and Meta-Heur_第3页
Optimization of Non-Linear Multiple Traveling Salesman Problem Using K-Means Clustering, Shrink Wrap Algorithm and Meta-Heur_第4页
Optimization of Non-Linear Multiple Traveling Salesman Problem Using K-Means Clustering, Shrink Wrap Algorithm and Meta-Heur_第5页
资源描述：

《Optimization of Non-Linear Multiple Traveling Salesman Problem Using K-Means Clustering, Shrink Wrap Algorithm and Meta-Heur》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、ISSN1749-3889(print),1749-3897(online)InternationalJournalofNonlinearScienceVol.8(2009)No.4,pp.480-487OptimizationofNon-LinearMultipleTravelingSalesmanProblemUsingK-MeansClustering,ShrinkWrapAlgorithmandMeta-HeuristicsR.Nallusamy1∗,K.Duraiswamy2,R.Dhanalaksmi3,

2、P.Parthiban41DepartmentofCSE,K.S.R.CollegeofTechnologyTiruchengode-637215,Tamilnadu,India2K.S.R.CollegeofTechnologyTiruchengode-637215,Tamilnadu,India3D-LinkIndiaLtd,Bangalore,India4Departmentofproductionengineering,NationalInstituteofTechnology,Tiruchirappalli

3、,India(Received29August2009,accepted27September2009)Abstract:ThispaperdealswithgeneratingofanoptimizedrouteformultipleTravelingSales-manProblems.Weusedamethodologyofclusteringthegivencitiesdependinguponthenum-berofsalesmenandeachclusterisallottedtoasalesman.?-M

4、eansclusteringalgorithmhasbeenusedforeasyclusteringofthecities.Inthiswaythe?TSPhasbeenconvertedintoTSPwhichissimpleincomputationcomparedtomTSP.Afterclustering,anoptimizedrouteisgeneratedforeachsalesmaninhisallottedcluster.Toachievethis,wefirstgeneratedaparentrou

5、teusingShrinkWrapalgorithmandthisparentstringisfurtheroptimizedbyusingtwootheroptimizingalgorithms.Forthispurpose,TabuSearchandSimulatedAnnealingwereextensivelyused.Fromtheresults,weobservedthatSimulatedAnnealinggenerateoptimizedroutecoveringlessdistancethanTab

6、usearch.Keywords:combinatorialoptimization;?-meansclustering;multipletravelingsalesmanprob-lem;simulatedannealingandTabusearch1IntroductionProblemsofcombinatorialoptimizationarecharacterizedbytheirwell-structuredproblemdefinitionaswellasbytheirhugenumberofaction

7、alternativesinpracticalapplicationareasofreasonablesize.Especiallyinareaslikerouting,taskallocation,orschedulingsuchkindsofproblemsoftenoccur.Theiradvantageliesintheeasyunderstandingoftheiractionalternativesandtheirobjectivefunction.UtilizingclassicalmethodsofO

8、perationsResearch(OR)oftenfailsduetotheexponentiallygrowingcomputationaleffort.Therefore,inpracticeheuristicsandmeta-heuristicsarecommonlyusedeveniftheyareunabletoguaranteea

当前文档最多预览五页，下载文档查看全文

此文档下载收益归作者所有

当前文档最多预览五页，下载文档查看全文
温馨提示：
1. 部分包含数学公式或PPT动画的文件，查看预览时可能会显示错乱或异常，文件下载后无此问题，请放心下载。
2. 本文档由用户上传，版权归属用户，天天文库负责整理代发布。如果您对本文档版权有争议请及时联系客服。
3. 下载前请仔细阅读文档内容，确认文档内容符合您的需求后进行下载，若出现内容与标题不符可向本站投诉处理。
4. 下载文档时可能由于网络波动等原因无法下载或下载错误，付费完成后未能成功下载的用户请联系客服处理。