Analyzes The Convergence And The Validity Of Genetic Algorithms

Genetic Algorithms is a type of universal searching and optimizing algorithms by simulating natural lives evolution. Genetic Algorithms is used by more users and in larger fields. This paper, firstly, introduces the history, the idea, the characteristic of Genetic Algorithms and the basic Genetic Algorithms. Secondly, this paper argues the convergence of Genetic Algorithms and introduces the analyzing convergence by Markov chain. With this understanding, this paper analyzes the convergence of Genetic Algorithms on the view of Information Convergence. Finally, this paper reviews the validity of Genetic Algorithms. On the view of algorithms complexity, this paper argues the limit of certainty algorithms that Turing Machine depicts and analyzes the validity of Genetic Algorithms that Probability Turing Machine depicts. This paper argues the validity of Genetic Algorithms comes from the high complexity that the uncertain part of Genetic Algorithms gives.