An Optimal Model for Stabilizing Net Financial Flow and Profit under Uncertainty in Build-Operate-Transfer Contracts

The objective of this research is to design an optimal model for Build-Operate-Transfer (B.O.T) contracts, considering uncertainty conditions. In this study, mathematical modeling was conducted using MATLAB software and the Particle Swarm Optimization method. Hypothetical data related to a combined cycle power plant project were analyzed as a case study. The construction cost of the power plant was estimated at $120 million, and it was projected that the project’s annual revenue would increase from $10.74 million in the fifth year to $46.64 million by the eighteenth year. Operating costs also rose from $1.68 million in the fifth year to $19.90 million by the thirtieth year. The results showed that the cumulative net financial flow for the government reached $273.32 million by the thirty-third year, while the private sector’s cumulative net financial flow increased to $157.66 million by the thirty-second year. The proposed model, using historical data and information obtained from similar projects, was able to reduce risks associated with revenue fluctuations and provide a more accurate prediction of annual profits. Based on the analysis, the internal rate of return (IRR) was calculated at 12% for the government and 25% for the private sector. Using the proposed model, the economic lifespan of the project was estimated to be 33 years from the government’s perspective and 32 years from the private sector’s perspective. The optimal point for transferring ownership of the project was determined to be in year 20.8. The findings indicated that the proposed model for B.O.T contracts, by reducing uncertainty and accurately forecasting financial flows and profits, serves as a suitable tool for improving financial decision-making in infrastructure projects.