This paper investegates evolution strategies of genetic algorithms. A kind of adaptive evolution strategies of genetic algorithms is presented
which combines basic genetic algorithms with local search scheme in genetic operation level and tunes the evolution strategies of genetic algorithms adaptively and controls the pressure of local search based on the genetic environment parameters. Its real implementation methods for TSP and the experiment results are introduced.