摘要
针对传统非线性方程组的解法对初始值敏感、收敛性差、精度低等问题,提出一种求解非线性方程组的混合量子遗传算法。该算法综合考虑了量子遗传算法和拟牛顿法的优点,充分发挥了前者的群体搜索和全局收敛性,并有效克服了后者的初始点敏感问题。数值模拟试验表明,该算法具有很高的精确性和收敛性,是求解非线性方程组的一种有效算法。
Aiming at the problems of the classical algorithms for solving the nonlinear equations such as high sensitivity to the initial value,poor convergence and low precision , a hybrid quantum genetic algorithm for solving nonlinear equations is proposed. The algorithm combined the advantages of quantum genetic algorithm and quasi--Newton method. It sufficiently exerted the advantages of the former such as group search, global convergence and effectively overcome the shortcoming of the latter such as sensitivity to the initial value. Numerical simulation experiments show that this algorithm has high precision and convergence characteristics, and is a reliable approach in solving the nonlinear equations.
出处
《微计算机应用》
2008年第7期1-5,共5页
Microcomputer Applications
关键词
非线性方程组
混合量子遗传算法
拟牛顿迭代法
进化计算
nonhnear equations, Hybrid Quantum Genetic Algorithm, quasi--Newton method, function optimization, evolutionary com- putation
