Generation expansion planning (also known as GEP) is finding an optimal solution for the planning problem in which the installation of new generation units satisfies both technical and financial limits. [1] [2] GEP is a challenging problem because of the large scale, long-term and nonlinear nature of generation unit size. [3] Due to lack of information, companies have to solve this problem in a risky environment because the competition between generation companies for maximizing their benefit make them to conceal their strategies. [1] Under such an ambiguous condition, various nonlinear solutions have been proposed to solve this sophisticated problem. [4] These solutions are based on different strategies including: game theory, [5] two-level game model, [6] multi-agent system, [1] genetic algorithm, [4] particle swarm optimization [7] and so forth.