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The Research On The Problem To The Time Float Of Probabilistic Network Model

Posted on:2011-05-21Degree:MasterType:Thesis
Country:ChinaCandidate:X H XieFull Text:PDF
GTID:2132330332460885Subject:Civil Engineering Management
Abstract/Summary:PDF Full Text Request
Network planning technology is a scientific method to make scheduled plan, and it is also an effective measure to manage a construction project. Now, for the research of uncertainty network planning technology, most is based on completion probability completion time estimation,critical path and criticalities of paths, mainly focus on the uncertainty of.the point and paths. Essentially, it is the analysis of path or path section duration. comparatively, the research to the uncertainty of work finish time is less,especially to time float, and time float is an important parameter and means to manage project using the network planning technique.So in view of the above situation, this article attempts to do some research on time float of uncertainty network planning especially the time float of probability network planning.According to the PERT method of probabilistic network model, presenting the definition of time float,mainly about the definition of path float and work float,and improve the solution of classics PERT, reached a new method to solve the time float of PERT. What is more, combined with the ideas of Monte Carlo method,put forward a method to solve the time float of PERT using Monte Carlo, both of the two method considered the uncertainty of work duration.According to the time float of PNM, this paper combined with the idea of stochastic dominance, presented the definition and solution of path float and work float to PNM. It does not constrained the assumption of PERT, more reflect the general condition.At last, by means of an example, calculate it's float using several kinds of method, and compared, reflect the characteristic of time float.
Keywords/Search Tags:Probabilistic network planning, time float, stochastic dominance
PDF Full Text Request
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