1 an average analysis of backtracking on random constraint satisfaction problems

1 an average analysis of backtracking on random constraint satisfaction problems

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时间:2019-02-28

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1、AnAverageAnalysisofBacktrackingonRandom*ConstraintSatisfactionProblemsKeXuandWeiLiNationalLaboratoryofSoftwareDevelopmentEnvironmentDepartmentofComputerScienceandEngineeringBeijingUniversityofAeronauticsandAstronautics,Beijing100083,P.R.China#Email:{

2、kexu,liwei}@nlsde.buaa.edu.cnAbstract.InthispaperweproposearandomCSPmodel,calledModelGB,whichisanaturalgeneralizationofstandardModelB.ThispaperconsidersModelGBinthecasewhereeachconstraintiseasytosatisfy.InthiscaseModelGBexhibitsnon-trivialbehaviour(nott

3、riviallysatisfiableorunsatisfiable)asthenumberofvariablesapproachesinfinity.Adetailedanalysistoobtainanasymptoticestimate(goodto1+o(1))oftheaveragenumberofnodesinasearchtreeusedbythebacktrackingalgorithmonModelGBisalsopresented.Itisshownthattheaveragenu

4、mberofnodesrequiredforfindingallsolutionsorprovingthatnosolutionexistsgrowsexponentiallywiththenumberofvariables.SothismodelmightbeaninterestingdistributionforstudyingthenatureofhardinstancesandevaluatingtheperformanceofCSPalgorithms.Inaddition,wefurthe

5、rinvestigatethebehaviouroftheaveragenumberofnodesasr(theratioofconstraintstovariables)varies.Theresultsindicatethatasrincreases,randomCSPinstancesgeteasierandeasiertosolve,andthebasefortheaveragenumberofnodesthatisexponentialinntendsto1asrapproachesinfi

6、nity.Therefore,althoughtheaveragenumberofnodesusedbythebacktrackingalgorithmonrandomCSPisexponential,manyCSPinstanceswillbeveryeasytosolvewhenrissufficientlylarge.Keywords.analysisofalgorithms,averagecomplexity,backtrackingalgorithms,CSP.*Researchsuppor

7、tedbyNational973ProjectofChinaGrantNo.G1999032701.#Forthefirstauthor,thereisapermanentemailaddressthatiske.xu@263.net.11.IntroductionAconstraintsatisfactionproblem(CSP)consistsofafinitesetU={u1,×××,un}ofnvariablesandasetofconstraints.Foreachvariableuado

8、mainDwithdelementsisiiispecified;avariablecanonlybeassignedavaluefromitsdomain.For2£k£naconstraintCi1,i2,×××,ikconsistsofasubset{ui1,ui2,×××,uik}ofUandarelationRi1,i2,×××,ikÍDi1´×××´Dik,wherei1,i2,×××,ikaredistinct.Ci1,i2,×××,iki

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