Application of a fuzzy set ranking method for project contingency estimating

Georgy, M, Barsoum, S and Basily, S 2004, 'Application of a fuzzy set ranking method for project contingency estimating', in Proceedings of the International Conference on Future Vision and Challenges for Urban Development, Cairo, Egypt, 20-22 December 2004.


Document type: Conference Paper
Collection: Conference Papers

Title Application of a fuzzy set ranking method for project contingency estimating
Author(s) Georgy, M
Barsoum, S
Basily, S
Year 2004
Conference name International Conference on Future Vision and Challenges for Urban Development
Conference location Cairo, Egypt
Conference dates 20-22 December 2004
Proceedings title Proceedings of the International Conference on Future Vision and Challenges for Urban Development
Publisher Housing and Building Research Center
Place of publication Egypt
Abstract A construction project is, no doubt, a risk-inherent endeavor. Industry practitioners have long been dealing with the project risks through number of means, most notably the adding of contingency amounts to their base cost estimates to account for the unfavorable future events. This is considered a fundamental risk mitigation practice in construction projects. Whenever a construction company fails to satisfactorily estimate the contingency amount, it risks getting the project on one hand and endangers its presumptive profits on the other hand. This may even lead, in some instances, to stoppage of work and/or bankruptcy. This paper introduces an application of a fuzzy set ranking method for the estimation of project contingencies. Fuzzy set ranking methods are generally based on the fuzzy sets theory developed by Lotfi Zadeh. The fundamentals of the fuzzy set ranking method adopted in this study have earlier been given in the literature. For practicality reasons, the method is being applied to the school building sector in Egypt. The selection of this particular sector is made due to the high level of standardization among the constructed facilities. Data for 30 construction projects in this sector were collected and used later, after proper preparation, for the calculation purposes. The paper then elaborates on the use of Monte Carlo simulation for the validation of the obtained results. Finally, the paper reports on the difference between the results from the fuzzy ranking method and Monte Carlo simulation. The difference generally turned out to be within an acceptable range.
Subjects Building Construction Management and Project Planning
Neural, Evolutionary and Fuzzy Computation
Keyword(s) Construction industry
contingency
business risk
cross impact method
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