Simple genetic algorithms have poor stability, for they are prone to premature
convergence. In order to overcome this disadvantage, a novel algorithm is proposed using a
combination of uniform design and genetic operation. A mapping between the solution space of
problems and the search space of the algorithm is established by coding, and then crossover
operation, mutation operation and uniform design are performed to produce the next generation of
solution candidates for iteration until convergence. The algorithm is tested with a typical testing
function, and proved feasible. Compared with the simple genetic algorithms, the algorithm proposed
in this paper has a higher precision and a faster convergence rate.