Risk analysis in construction networks using a modified stochastic model.

Guo, Qiu Ling, Maher, Mike and Wamuziri, Sam (2001) Risk analysis in construction networks using a modified stochastic model. Civil Engineering and Environmental Systems, 18 (3). 215 - 241. ISSN 1028-6608

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    A review of construction network analysis indicates that new methods are needed for quantifying risks in project evaluation. The paper proposes a new analytical method, the Modified Stochastic Assignment Model (MSAM), for the prediction of project duration. The proposed method is inspired by a previous method used solely in traffic networks, the Stochastic Assignment Model (SAM). The MSAM method applies Clark's approximation to find the longest project duration. Two cases are used to demonstrate the validity and application of the MSAM in construction project evaluations. The accuracy of the MSAM is assessed by comparing it with the Monte Carlo Simulation (MCS). A comparison of the MSAM with other methods, such as PERT and PNET, has also been presented. It is found that the new method is an analytical counterpart of the MCS and is very efficient in saving computational time whilst taking full account of the correlations between paths.

    Item Type: Article
    Print ISSN: 1028-6608
    Electronic ISSN: 1029-0249
    Uncontrolled Keywords: Risk; Construction networks; Modified Stochastic Assignment Model; MSAM; Project duration; Prediction; Clark's approximation; Comparisons; Monte Carlo Simulation; PERT; PNET; Evaluation;
    University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Engineering and the Built Environment
    Dewey Decimal Subjects: 600 Technology > 690 Building & construction > 692 Auxiliary construction practices
    500 Science > 510 Mathematics > 515 Analysis
    Library of Congress Subjects: T Technology > TH Building construction
    Q Science > QA Mathematics
    Item ID: 2021
    Depositing User: RAE Import
    Date Deposited: 17 Mar 2008 15:14
    Last Modified: 27 Aug 2013 09:53

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