Use of evolutionary algorithm in the investment projects evaluation an application on the infrastructure project within the context of build operate transfer model

In the realization of infrastructure projects, the interest shown in the Build-Operate-Transfer (BOT) model is on the increase. Through the BOT projects, the risks and awards of the public in the realization of infrastructure projects are transferred to the private sector. Implementing the BOT projects successfully depends on the ability to constitute a structure which enhances the possibilities of the sponsors' achievement in the BOT tender and the finding debt for the external fund need. The debt to equity ratio, the concession length and the price variables are the critical financial factors in BOT projects. Thus, these factors must be designed in the way that they will also look out for the interests of the participants of the project as well as the project sponsors. The purpose of this study is to develop financial optimization models meeting all the necessary financial constraints and determining the optimum combination of the critical financial factors under a reasonable level of profit marjin for the decision-makers at the stage of BOT project appraisal taking place in the wake of the completion of the feasibility study of BOT investment project. These models in question, are, from the viewpoint of project sponsors, the combination of financial models and the optimization models comprising the objectives to maximize the potential of winning the BOT tender and finding loan. In this study, a new approach regarding the project finance has been put forth by optimally integrating the major financial factors that provide financial viability for the project. The optimization equations and constraints were developed on the basis of the discounted cash flow analysis which is among the dynamic methods, and the calculations were made by utilizing the real-coded Evolutionary Algorithm for the non-linear behaviour of the objective function. In this way, a more efficient and productive support is provided for the financial decision-making process.