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Resource Strategies For Dynamic Construction Project Management (network, Precedence).

dc.contributor.authorMorua Padilla, Eloy
dc.date.accessioned2016-08-30T16:39:58Z
dc.date.available2016-08-30T16:39:58Z
dc.date.issued1986
dc.identifier.urihttp://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:8621344
dc.identifier.urihttps://hdl.handle.net/2027.42/127921
dc.description.abstractA Monte Carlo based computer simulation model, called DYNASTRAT, was developed to model the dynamics of applying a resource allocation strategy to sample time and cost of uncertain construction projects. DYNASTRAT models time and cost as random variables, as well as dependencies among construction activities, and among activities and their cost. It uses project progress to date, and outcomes of such random variables as equipment productivity and worker cost per day, to forecast duration and cost of the remainder of the project. DYNASTRAT develops a method to describe management strategies for uncertain projects. The method gives construction managers a flexible tool to define priority of activities and resources and simulate real time allocation decisions. DYNASTRAT models assignment of resources under uncertainty, permits variability in the level of resources that can be allocated to activities, and allows interruption of activities in progress and reassignment of their resources to activities of higher priority. It also monitors and updates planned delivery dates for major pieces of equipment.
dc.format.extent220 p.
dc.languageEnglish
dc.language.isoEN
dc.subjectConstruction
dc.subjectDynamic
dc.subjectManagement
dc.subjectNetwork
dc.subjectPrecedence
dc.subjectProject
dc.subjectResource
dc.subjectStrategies
dc.titleResource Strategies For Dynamic Construction Project Management (network, Precedence).
dc.typeThesis
dc.description.thesisdegreenamePhDen_US
dc.description.thesisdegreedisciplineApplied Sciences
dc.description.thesisdegreedisciplineCivil engineering
dc.description.thesisdegreegrantorUniversity of Michigan, Horace H. Rackham School of Graduate Studies
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/127921/2/8621344.pdf
dc.owningcollnameDissertations and Theses (Ph.D. and Master's)


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