Recently, research papers which are related to artificial intelligence topic, especially decision support methodologies have received continuous concentration and achieved remarkable developments. Many articles have shown the important application of those methods in several aspects along with their effectiveness in most fields of research. In this paper we focus on approach using genetic algorithm and Nash equilibrium to solve the problem choosing appropriate bidders in multi-round procurement, which is currently considered an unsolved problem to many procuring entities. Instead of using manual and subjective consideration from procuring entities, a scientific methodology on decision-making support has been studied and identified equilibrium points in multiple-round procurements, which is the most beneficial to both investors and selected tenderers. These results can be a scientific promising solution for choosing bidders in multi-round procurement and ensure win-win relationship for all parties in procurement process.