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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 109
PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON SOFT COMPUTING TECHNOLOGY IN CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING
Edited by: Y. Tsompanakis, J. Kruis and B.H.V. Topping
Paper 16

Analysing Build-Operate-Transfer Models in Utility Projects

N. Shahrara1, T. Çelik2 and A.H. Gandomi3

1Department of Civil Engineering, Eastern Mediterranean University, Northern Cyprus
2Department of Civil Engineering, Cyprus International University, Nicosia, Northern Cyprus
3Department of Civil Engineering, The University of Akron, United States of America

Full Bibliographic Reference for this paper
N. Shahrara, T. Çelik, A.H. Gandomi, "Analysing Build-Operate-Transfer Models in Utility Projects", in Y. Tsompanakis, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Fourth International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 16, 2015. doi:10.4203/ccp.109.16
Keywords: public-private-partnership, build-operate-transfer, water projects, sewer projects, rehabilitation, financial analysis, genetic programming, gene expression programming.

Summary
In this paper the financial viability of undertaking build-operate-transfer (BOT) contracts for sewer and water projects in California, United States of America is analysed. Furthermore with the aid of sensitivity analysis, risk parameters are identified. Sensitivity analysis results demonstrate that project construction cost determines the financial viability of undertaking a BOT contract; therefore, reliable construction cost prediction, based on limited information, at the early stages of the project planning phase is crucial for development of an objective BOT agreement. This study utilizes gene expression programming (GEP), an extension of the genetic algorithm and genetic programming, to develop a prediction model for estimating the construction cost of water and sewer rehabilitation/replacement projects. A database used for developing the model was established on the basis of data related to 210 water and sewer projects obtained from the City of San Diego, California, United States of America.

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