Using an Adaptive Genetic Algorithm to Improve Finance Decision

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摘要 Optimisingbothqualitativeandquantitativefactorsisakeychallengeinsolvingconstructionfinancedecisions.Thesemi-structurednatureofconstructionfinanceoptimisationproblemsprecludesconventionaloptimisationtechniques.Withadesiretoimprovetheperformanceofthecanonicalgeneticalgorithm(CCA)whichischaracterisedbystaticcrossoverandmutationprobability,andtoprovidecontractorswithaprofit-risktrade-offcurveandcashflowprediction,anadaptivegeneticalgorithm(AGA)modelisdeveloped.TenprojectsbeingundertakenbyamajorconstructionfirminHongKongwereusedascasestudiestoevaluatetheperformanceofthegeneticalgorithm(CA).TheresultsofcasestudyrevealthattheACAoutperformedtheCGAbothintermsofitsqualityofsolutionsandthecomputationaltimerequiredforacertainlevelofaccuracy.TheresultsalsoindicatethatthereisapotentialforusingtheGAformodellingfinancialdecisionsshouldbothquantitativeandqualitativefactorsbeoptimisedsimultaneously.
机构地区 不详
出版日期 2004年03月13日(中国期刊网平台首次上网日期,不代表论文的发表时间)
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