一种基于元胞自动机的改进遗传算法

A Cellular Automata Based on Improved Genetic Algorithm

针对遗传算法中存在搜索效率和解精度低的问题,结合元胞自动机模型,提出了一种改进的遗传算法——竞争杂交算法。在适应度函数中运用元胞自动机模型进行竞争复制,在确定交叉算子时进行杂交,依此来对遗传算法进行改进。仿真结果表明,竞争杂交算法在搜索速度和概率上比简单遗传算法要高一些。

In view of the existence of genetic algorithm search efficiency in the reconciliation problem of low accuracy,it is combined with cellular automaton model,an improved genetic algorithm-hybrid algorithm competition.Fitness function in the application of cellular automaton model is used to compete with copy for determining the hybridized crossover midnight to improve the genetic algorithm.Simulation results show that the hybrid algorithm competition in the search speed and the probability is higher than that of a simple genetic algorithm.