Statistical Genetic Algorithm
Mohammad Ali Tabarzad, Caro Lucas, Ali Hamzeh · Zenodo (CERN European Organization for Nuclear Research) · 2008
Adaptive Genetic Algorithms extend the Standard Gas to use dynamic procedures to apply evolutionary operators such as crossover, mutation and selection. In this paper, we try to propose a new adaptive genetic algorithm, which is based on the statistical information of the population as a guideline to tune its crossover, selection and mutation operators. This algorithms is called Statistical Genetic Algorithm and is compared with traditional GA in some benchmark problems.