THE STATISTICAL GENETIC ALGORITHMS
统计遗传算法

The deficiency of the schema theory in GA(genetic algorithms) and its improvement are discussed in this paper. The similarity between GA and heuristic search algorithm (a algorithm) and the probabilistic properties of GA are analyzed as well. Form the discussion, the similarity between GA and SA (statistical heuristic search) proposed by the authors is discovered. Therefore, when transferring the theory and results of SA to GA, a new statistical genetic algorithm can be established. In order to adapt to optimization computation, the maximal statistic and its corresponding SA called SMA are introduced. By combining the SMA and GA, a new algorithm SMA(MAX) is obtained. Using the new algorithm, the prematurity in general GAs can be overcome. The new algorithm also provides the possibility for parallel computing and a powerful tool for quantitative analysis of accuracy, confidence and computational complexity of GA.