An Improved Genetic Algorithm Based on J1 Subdivision and Fixed Point Theory

In this paper an improved genetic algorithm is proposed to solve optimal problems applying fixed point algorithms of continuous self-mapping in Euclidean space. The algorithm operates on a J1 subdivision of searching space and generates the integer labels at the vertices, The nature reproduction by fission phenomenon introduction genetic algorithm, proposes one kind of improvement genetic algorithm, This algorithm has avoided searching the solution space repeated and achieved the optimal solution. The result illustrate that the proposed algorithm have global optimization capability, computing efficiency and strong stability.