Chapter
Aug 14, 2017
International Conference on Construction and Real Estate Management 2016

Risk Analysis in the Subcontractor Selection Process for International Construction Projects

Publication: ICCREM 2016: BIM Application and Off-Site Construction

ABSTRACT

Subcontracting is a very common practice in the construction industry. Subcontractors perform the actual production work in most of the construction projects. Selection of subcontractors for the work packages is generally made based on a deterministic manner. However, a real-life construction project is full of risks and uncertainties. The objective of this study is to account and incorporate risks into the subcontractor selection problem by performing Monte-Carlo simulation method in order to make better decisions under uncertainty. This study is mainly based on the findings of a previous study. In the previous study, the selection of subcontractors for all work packages in the studied real-life construction project was made using genetic algorithm technique considering time, cost, and quality performances, and six different optimal subcontractor combinations and their related three deterministic project performances were identified. In this study, risk analysis of these subcontractor combinations is performed and the probabilistic distributions of time, cost, and quality performances are obtained. The probabilistic solutions of optimal subcontractor combinations are used to make a decision in a more realistic way.

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REFERENCES

Dunn, W.L. and Shultis, J.K. (2012). “Exploring Monte Carlo methods.” Exploring Monte Carlo Methods, 15(2012), 3–3.
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Kwak, Y.H. and Ingall, L. (2007). “Exploring Monte Carlo simulation applications for project management.” Risk Management, 9(1), 44–57.
Loyd, A.A. (2006). A Comparison of Fuzzy Indices With Monte Carlo Simulations for Risk Assessment at the Preliminary Stages of Transit Project Planning. Oklahoma State University, Oklahoma, U.S., 8–12.
Marom, S. (2010). “Project risk management and the application of Monte Carlo simulation.” <http://quantmleap.com/blog/2010/07/project-risk-management-and-the-application-of-monte-carlo-simulation> (March. 11, 2016).
Polat, G., Kaplan, B. and Bingol, B.N. (2015). “Subcontractor selection using genetic algorithm.” Procedia Engineering, 123(2015), 432–440.
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Information & Authors

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Published In

Go to ICCREM 2016
ICCREM 2016: BIM Application and Off-Site Construction
Pages: 1285 - 1292
Editors: Yaowu Wang, Ph.D., Professor, Harbin Institute of Technology, Mohamed Al-Hussein, Ph.D., Professor, University of Alberta, Geoffrey Q. P. Shen, Ph.D., Professor, The Hong Kong Polytechnic University, and Yimin Zhu, Ph.D., Professor, Louisiana State University
ISBN (Online): 978-0-7844-8027-4

History

Published online: Aug 14, 2017

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Authors

Affiliations

Befrin Neval Bingol [email protected]
Ph.D. Candidate, Dept. of Civil Engineering, Istanbul Technical Univ., Istanbul, Turkey, 34469. E-mail: [email protected]
Associate Professor, Dept. of Civil Engineering, Istanbul Technical Univ., Istanbul, Turkey, 34469. E-mail: [email protected]

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