Integrating System Dynamic and Fuzzy Logic for Economic Assessment of BOT Projects

Document Type : Original Article

Authors

1 Assistant Professor, Department of Civil Engineering, Faculty of Engineering, Payame Noor University

2 Assistant Professor, Department of Civil Engineering, Iran University of Science and Technology

3 PhD. Student in Construction Management, Department of Civil Engineering, Iran University of Science and Technology

Abstract

The selection of the most appropriate project for the investment is one of the most important decisions that should be made by the private investors. This problem is of vital importance in BOT projects, where the total investment as well as the investor's profit should be recovered by the project's income. There are several approaches proposed by the researchers to determine the best economical project in comparison to other projects. The previous researches, however, faced with some major defects. As an example, the effects of various factors affecting the project evaluation process as well as the existing risks and uncertainties are not taken into account. In this research, economic assessment of BOT projects is performed by integrating system dynamic simulation approach and fuzzy logic. For this purpose, first the project's NPV is modeled considering all the influencing factors qualitatively. The relationships that exist between different factors are then determined and the quantitative model is built. Using the developed model, the value of NPV is simulated considering the effects of all the influencing factors and the existing uncertainties. Finally, the value of project's NPV is determined as a triangular fuzzy number. Finally, the best alternative project is selected by comparing the simulated values of NPV. To evaluate the capabilities and performance of the proposed model, the project economical evaluation is performed for two highway projects and the best project is selected.

Keywords

References

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History

  • Receive Date: 05 March 2015
  • Revise Date: 30 November 2015
  • Accept Date: 05 March 2016

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