基于混沌遗传算法的故障测试集最小化方法

A Minimization Approach for Fault Test Set Based on Chaos Genetic Algorithm

利用混沌序列的随机性、遍历性及规律性等特点来控制遗传算法中交叉与变异操作 ,即混沌交叉与混沌变异 ,提出了一种改进的遗传算法——混沌遗传算法 ,并针对数字集成电路的故障完备测试集的最小化问题的具体特点 ,分析并设计了基于混沌遗传算法的故障测试集最小化方法 ,仿真实验验证了该方法的高效性与实用性 ,其性能明显优于标准遗传算法。

Chaotic sequences which take on stochastic,ergodic and regular properties at the same time,is utilized for controlling crossover operation and mutation operation in genetic algorithm,which is called chaotic crossover and chaotic mutation.Based on above,a improved genetic algorithm,called chaos genetic algorithm,is presented.Afterwards,considering the characteristic of the minimization of complete fault test set for digital integrate circuit,a minimization approach for fault test set based on chaos genetic algorithm is studied and designed.The simulation results confirm the high efficiency and practicability of the proposed approach,which is superior to the standard genetic algorithm.