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1、外文翻译EnvironmentalModelling&Software1.1.BackgroundEnvironmentalchange,economicandsocialpressures,andlimitedresourcesmotivatesystemsanalysistechniquesthatcanhelpplannersdeterminenewmanagementstrategies,developbetterdesignsandoperationalregimes,improvea
2、ndcalibratesimulationmodels,andresolveconflictsbetweendivergentstakeholders.Metaheuristicsareemergingaspopulartoolstofacilitatethesetasks,andinthefieldofwaterresources,theyhavebeenusedextensivelyforavarietyofpurposes(e.g.modelcalibration,theplanning,
3、designandoperationofwaterresourcessystemsetc.)inmanydifferentapplicationareasoverthelastfewdecades(Nicklowetal.,2010).Sincemetaheuristicswerefirstappliedinthewaterresourcesfield(DoughertyandMarryott,1991;McKinneyandLin,1994;Ritzeletal.,1994;Guptaetal
4、.,1998),theirpopularityhasincreaseddramatically,probablyfacilitatedbythesimultaneousincreaseofavailablecomputationalpower(Washingtonetal.,2009),tothepointwheretheyarewidelyused(Nicklowetal.,2010),evenbyactualwaterplanningutilities(Basdekas,2014).Zuff
5、erey(2012)definesametaheuristic“asaniterativegenerationprocesswhichguidesasubordinateheuristicbycombiningintelligentlydifferentconceptsforexploringandexploitingthesearchspace”,aspartofwhich“learningstrategiesareusedtostructureinformationinordertofind
6、efficientlynear-optimalsolutions.”Unlikemore“traditional”approaches,whichusemathematicalprogrammingtospecifytheoptimalvalueofoneormoreobjectivefunctions,metaheuristicsincorporateelementsofstructuredrandomnessforsearchandfollowempiricalguidelines,ofte
7、nmotivatedbyobservationsofnaturalphenomena(ColletteandSiarry,2003).Metaheuristicscanbedividedintotwogroups,includingpopulation-basedalgorithms(e.g.geneticalgorithms,evolutionarystrategies,particleswarmoptimization,antcolonyoptimization,etc.)andsingle
8、point-basedmethods(e.g.simulatedannealing,tabusearch,simple(1+1)evolutionarystrategies,trajectoryorlocalsearchmethods,etc.).Evolutionaryalgorithms(EAs)arethemostwell-establishedclassofmetaheuristicsforsolvingwaterresourcesproblemsandareinspiredbyvari