A socio-economic multi-objective optimization approach toward enhancing public–private partnerships’ concession agreements in infrastructure development

Abstract

The participants of the public–private partnership projects have different parts in developing the concessions, hence different perspectives and goals. Besides, the public–private partnership concession agreement has many parameters and components, and a change in one component will have a considerable impact on other components. Thus, determining the optimal value for different concession parameters by providing a series of feasible contribution options was investigated in this paper using two different multi-objective optimization models: genetic algorithm and Thompson sampling. Two case studies (the US I-495 and the I-4 Ultimate) were used to construct and validate the results of the model. The model results showed that the socio-economic sustainability performance increases as the private equity increases and the public equity decreases. The results also showed that the socio-economic sustainability performance increases as the concession price (user-fee) decreases. Having these contribution options could facilitate the decision-making process for both the public and private parties. The genetic algorithm model obtained faster optimization results when compared to the Thompson sampling model; however, the Thompson sampling obtained better results. Moreover, the use of the model could improve the socio-economic sustainability performance of the public–private partnership projects.