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Schedule Delay Risk Analysis in Construction Projects with a Simulation-Based Expert System

Autor(en):



Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Buildings, , n. 8, v. 10
Seite(n): 134
DOI: 10.3390/buildings10080134
Abstrakt:

In this paper, we present a simulation-based approach for effectively estimating delay risks in project schedules and predicting the possibilities of in-time project completion for various deadlines. The main contribution of this study is the development of a novel approach for duration risk quantification, which uses a newly introduced equation for total risk estimation regarding activities’ durations, and quantifying the manager’s experience as expressed through a questionnaire. In addition, the proposed approach integrates these preferences into a simulation-based framework used for estimating the activities’ durations variation and predicting the actual project duration with more accuracy. Furthermore, using different distributions according to each activity characteristic supports decision making from a wide range of experts, from risk-averse to risk-seeking managers. The proposed method was applied to estimate the total project completion time of a complicated hotel renovation project and the possibility for the project to be delivered within an imposed deadline. The promising results in comparison to the classic PERT method proved that this process can better express the uncertainty and provide project risk managers with better predictions when estimating budget and time-critical overruns under lack of knowledge and historical data.

Copyright: © 2020 by the authors; licensee MDPI, Basel, Switzerland.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10427463
  • Veröffentlicht am:
    24.07.2020
  • Geändert am:
    02.06.2021
 
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