NUMERICAL SOLUTIONS FOR STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS VIA ACCELERATED GENETIC ALGORITHM

This paper introduced a new accelerated Genetic Algorithms (GAs) method to find a numerical solutions of stochastic Partial differential equations driven by space-time white nose wiener process . The numerical scheme is based on a representation of the solution of the equation involving a stochastic part arising from the noise and a deterministic partial differential equation . By using Doss-Sussmann transformation that enables us to work with a partial differential equation instead of the stochastic partial differential equation. Then compare these solutions obtained by our method with saul'yev method and deterministic solution.