Optimisingbothqualitativeandquantitativefactorsisakeychallengeinsolvingconstructionfinancedecisions.Thesemi-structurednatureofconstructionfinanceoptimisationproblemsprecludesconventionaloptimisationtechniques.Withadesiretoimprovetheperformanceofthecanonicalgeneticalgorithm(CCA)whichischaracterisedbystaticcrossoverandmutationprobability,andtoprovidecontractorswithaprofit-risktrade-offcurveandcashflowprediction,anadaptivegeneticalgorithm(AGA)modelisdeveloped.TenprojectsbeingundertakenbyamajorconstructionfirminHongKongwereusedascasestudiestoevaluatetheperformanceofthegeneticalgorithm(CA).TheresultsofcasestudyrevealthattheACAoutperformedtheCGAbothintermsofitsqualityofsolutionsandthecomputationaltimerequiredforacertainlevelofaccuracy.TheresultsalsoindicatethatthereisapotentialforusingtheGAformodellingfinancialdecisionsshouldbothquantitativeandqualitativefactorsbeoptimisedsimultaneously.
