用实数编码遗传算法解非线性方程组

Real-code Genetic Algorithms for Solving Systems of Nonlinear Equations

将非线性方程组的求解问题转化为求最大值问题,设计出选择算子,杂交算子,变异算子,加速收敛的最佳个体保留策略和预防早熟的灭绝与移民算子,利用实数编码遗传算法求出了非线性方程组的解,数值例子表明了该方法的有效性。

This paper represents a method for solving systems of nonlinear equations. Firstly, we transform them into numeric problems of least square approximation. Then, we give some operators of selection, crossover and mutation; we also give strategies of the best individual reservation for convergence speedup, and operators of depopulation and emigration for preventing prematurity. By applying real code genetic algorithm we solved the problem. The results of numerical simulation show the efficiency of the method.