ortionoftheenergylotocompreors.however,foralongtimeperiod,researchershavemademostpartoftheireffortsonstudyinghowtoimprovethemostimportantparts,theimpellers,ofthecompreors,whilestudiestothestationarypartsareverylimited.sincetherequirementsoftheimprovementontheperformancesoftheenergy-savingcompreorsarealwayscontinued,theresearchershavenochoicebuttoturntheirsighttothestationaryparts,expectingtofindnewenergy-savingpoibilitiessoastoincreasethetotalmachines’efficiencyfurther.coequently,howtodesignthehighefficientstationarypartsthatcanhaveaminim

umenergyloisanurgenttaskfacedbytheresearchersofcentrifugalcompreors.
geneticalgorithms(gas),rapidlydevelopedinrecentyears,areregardedasstochasticsearchtechniquesthatmimicnaturalselectionanddarwin’smainprinciple:survivalofthefittest.gasaimtofinethebestsolutiotoaproblembygeneratingacollection(“population”)ofpotentialsolutio(“individual”).bettersolutioarehopefullygeneratedthroughcertaingeneticoperatiosuchasselection,crooverandmutationfromthecurrentsetofpotentialsolutio.theproceisrepeateduntilanacceptablesolutionisfound.gashavemanyadvantagesoverothersearchtechniques.theseinclude:1)robustne,gasarecomputationallysimpleandpowerfulinthesearchforimprovementandhavenolimitationonthesearchace.2)intriicparallelism,gascarryoutsearchthroughpopulatioofpoints,notsinglepoint,whichmakesthemintriicallyparallel.3)globalproperty,gasuserandomoperationintheirevolutionproceesthatallowawiderexplorationofthesearchace,andhenceitislikelythattheexpectedgasol

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