Merging Nash Equilibrium Solution with Genetic Algorithm : The Game Genetic Algorithm

Abstract

In this paper, it has been integrated Nash Equilibrium solution of Game Theory with Genetic Algorithms (GA) to optimize performance of a job scheduler, in order to simulate topology and sizing of Analog Electrical Circuits simulation. We proposed a new method for performance problems solving of Genetic Algorithms applied to Electronic Design Automation (EDA) simulator tool optimization. This optimal solution process is formulated as a non-cooperative Game in order to solve GA performance problem more efficiently and effectively. For these reasons, it has been created a new integrated Algorithm named Game Genetic Algorithm (GGA). A flow chart of the algorithm is presented to investigate the feasibility of the above approach.