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AbstractAbstract|Figures/TablesFigures/Tables|ReferencesReferences
Abstract
ThisstudyinvestigatesthepracticalandfinancialimplicationsofalternativestrategiesformeetingexplicitconservationgoalsontheAgulhasPlain,SouthAfrica.Thisisanareaofexceptionalbiodiversityincreasinglythreatenedbyalienplantinfestation,urbanisation,andagriculturalexpansion.Inadditiontotraditionalon-reserveprotection,weidentifytwotypesofproperty-rightsagreements(conservationeasementsandmanagementagreements)andtwotypesoffinancialincentives(landmanagementassistanceandtaxrelief)asappropriateforencouragingoff-reserveconservationontargetedlandsinthearea.Specifically,wesuggestactionstooffsetthecostsfacinglandownersundernewpiecesoflegislation,suchasalien-clearingrequirementsandapropertytax.AfterrefininganexistingGISdatabaseofcadastralunitstargetedforconservation,weassignedon-oroff-reserveconservationstatustopropertiesonthebasisofasimpledecisionsystem,whichtooktheirreplaceabilityoftheareaintoaccount.Threeimplementationscenariosweredesigned:
anentirely‘on-reserve’approach,amixedon-andoff-reserveapproach,andthemixedapproachinconjunctionwithfinancialincentives.Theconservationcosts,toboththepublicandprivatesector(includingexpandedobligationsfromnewlegislation),werefirstmodelledandthenanalysedinaGeographicInformationSystem.Wefoundthatatraditionalon-reserveapproachwouldcostthestateaboutR240Minacquisitioncosts,whereasbothmixedapproaches,usingthedecisionrulesdevelopedinthisstudy,wouldinvolveleaving40%oftargetedareasinprivatehands,savingthestate80%inacquisitioncosts.Ofthesubsequentconservationcosts,whichtotalR401M(presentvalue@6%discountrate;
Scenario1),mostarealienclearingcosts.Sincelandownersarenowcompelledtoputupthesecosts,thestatecouldmakefurthersavings(44–51%)underamixedmanagementscenario.UsingPropertyRatereliefasanadditionalfinancialincentiveisrelativelyefficientinthatitmaysavetargetedprivatelandowners32%inPropertyRates,atacostof5.5%ofexpectedtaxrevenuetothestate.Giventheprohibitivecosts,realisingconservationgoalsintheAgulhasPlainwillprobablydependupontheestablishmentofinstitutions,mechanisms,andincentivesforprivateparticipationinconservation.
ArticleOutline
1.Introduction
2.Identificationofappropriateconservationtoolsandfinancialincentives
2.1.Property-rightsmechanisms
2.2.Financialincentives
3.Methods
3.1.Spatialdataandtargetedconservationareas
3.2.Scenariodevelopment
3.3.Assigningappropriatetoolstoindividualproperties:
adecisionsystem
3.4.Financialimplicationsofalternativeconservationstrategies
3.4.1.Acquisitioncosts
3.4.2.Managementcosts
3.4.2.1.Generalmanagement
3.4.2.2.Alienclearingcosts
3.4.2.3.Firepreventioncosts
3.4.3.Propertytaxes
3.4.4.Effectoffinancialincentives
3.5.Aggregationanddistributionofcosts
4.Results
4.1.Assigningconservationmechanismstotargetedcadastralunits
4.2.Implicationsofalternativeconservationstrategiesatthecadastrallevel
4.3.Financialimplicationsofalternativeconservationstrategiesattheaggregatelevel
4.3.1.Acquisition
4.3.2.Generalmanagement
4.3.3.Alienclearingcosts
4.3.4.Firepreventioncosts
4.3.5.Taxreliefasafinancialincentive
4.3.6.Summaryoffinancialimplicationsforthestate
5.Discussion
5.1.Assigningconservationmechanismstotargetedproperties
5.2.Financialimplicationsofimplementingalternativeconservationstrategies
Acknowledgements
References
127
Heuristicsfordemand-drivendisassemblyplanning
Computers&
OperationsResearch,Volume34,Issue2,February2007,Pages552-577
IanM.Langella
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Remanufacturingofusedproductshasbecomeacceptedasanadvantageousdispositionoptionwithinthefieldofreverselogistics.Remanufacturing,whereafirmtakesreturnedproductsattheendoftheirlifeanddisassemblesthemtoobtainpartswhicharereassembledinto“goodasnew”products,mayrequireso-calleddemand-driven-disassembly,whereaspecificamountofreturnedproductsmustbedisassembledtoyieldpartswhichareeitherdemandedexternally,orusedintheremanufacturingoperation.Whileinitssimplestform,thesolutioncanbemerelycalculated,morerealisticallycomplexproductstructuresrequireamorepowerfulsolutionmethod.Thefirstchoice,integerprogramming(IP)canbeusedtoarriveatanoptimalsolution,withthedisadvantagethatthetimerequiredtosolvetheproblemexplodeswithincreasinglycomplexproductstructuresandlongertimehorizons.Anotherpossiblemethod,heuristicswhichwerepresentedinapreviousworkonthisproblem[TalebandGupta(Computers&
IndustrialEngineering1997;
32(4):
949–61],offerafaster,easiersolutionwiththedisadvantagethatitisnotnecessarilyoptimal,andundercertaincircumstancesmaydeliveraninfeasibleresult.Inthiswork,thisproblemwascorrectedandtheheuristicwasextendedinseveralimportantwaystodealwithholdingcostsandexternalprocurementofitems.Themethodologyisillustratedbyanexample.Anotheradvantageoftheheuristicisthatitcanbeprogrammedintocodeandexecutedviaspreadsheetapplication,whichwillfacilitateitsapplication.Aperformancestudyrevealsthatthenewheuristicperformsquitewellforawidespectrumofrandomlygeneratedproblemtestinstances.
2.Problemdescription
2.1.Setting
2.2.Basicproblem
2.3.Morerealisticproblem
2.4.Relevantcosts
2.4.1.Coreprocurementcosts
2.4.2.Separationcosts
2.4.3.Holdingcosts
2.4.4.Leafprocurementcosts
2.4.5.Disposalcosts
2.5.Problemstatement
2.6.Literaturereview
3.Exactmethod
3.1.Assumptionsandnotation
3.2.Modelandobjectivefunction
4.Heuristicapproach
4.1.Overview
4.1.1.CoreAlgorithm
4.1.2.AllocationAlgorithm
4.2.Examplesillustratinginfeasibility
4.3.Suggestedimprovement
4.3.1.Improvementforinfeasibilityproblem
4.3.2.Incorporatingholdingcostsintotheapproach
4.3.3.Incorporatingexternalleafprocurement
4.3.4.Extensiontodeliberateleafholdingversusdisposal
4.3.5.Numericalexample
4.3.6.Critique
4.4.Performancestudy
4.4.1.Experimentaldesign
4.4.2.Results
5.Conclusionandoutlook
128
Canfamily-planningprograms“cause”asignificantfertilitydeclineincountriescharacterizedbyverylowlevelsofsocioeconomicdevelopment?
NewevidencefromBangladeshbasedondynamicmultivariateandcointegratedtime-seriestechniques,1965–1991
JournalofPolicyModeling,Volume19,Issue4,August1997,Pages441-468
AbulM.M.Masih,RumiMasih
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AbstractAbstract|ReferencesReferences
Unlikemostempiricalworksonfertilityanalysis,thisstudyinvestigatesthequestionastowhetherfamily-planningprogramscan“cause”asignificantfertilitydeclineinacountrycharacterizedbyverylowlevelsofsocioeconomicdevelopment.Theanalysisisbasedontheapplicationofthefollowingdynamictime-seriestechniquesinamultivariatecontext:
cointegration,vectorerror-correctionmodeling,variancedecompositions,andimpulseresponsefunctions.ThesefourdynamictoolsarerecentlydevelopedandhithertountriedinfertilityanalysisinthecontextofapoordevelopingeconomysuchasBangladesh.Ourfindingsappeartobeconsistentwiththenewtheoreticalviewthatholdsthatfertilitydeclinemayresultfromeitheroftwodistinctdevelopmentalphases,oneshort-termandtheotherlong-term.Accordingtothisview,thesecondphase(comprisingthe“sufficient”conditionforfertilitydecline)incorporatestheconventionalviewthatinthelongterm,fertilitydeclinemayresultfromacomplexdynamicinteractionwithorganizedfamilyplanningandsignificantsocioeconomicstructuralchange.Incontrast,thefirstphase(comprisingthe“necessary”conditionforfertilitydecline)maynotneedsuchsignificantstructuralchangeinordertoeffectfertilitydeclineintheshortterm.Allitmayrequireisapredominantlyclient-oriented,affordable,persuasive,andwell-organizedfamily-planningprogram—aprogramthatisfirmlysupportedbythepoliticalandsocialeliteatalllevelsofthatsociety,aswellasbeingadaptedtothesocioculturalrealitiesofthevastmassesofthepeopleofthatregion.
•References
129
WhatmakesasuccessfulvolunteerExpertPatientsProgrammetutor?
Factorspredictingsatisfaction,productivityandintentiontocontinuetutoringofanewpublichealthworkforceintheUnitedKingdom
PatientEducationandCounseling,Volume75,Issue1,April2009,Pages128-134
WendyMacdonald,EvangelosKontop