浮点遗传算法中一种新的杂交算子

New crossover operator in float-point genetic algorithms

为了提高浮点遗传算法在优化计算时向最优解收敛的速度 ,提出了一种新的遗传算子 :代间差分杂交算子 .通过应用于非线性参数估计的仿真计算 ,表明了这种杂交算子的有效性及其相对于普通杂交算子的优点 .

To improve the convergent speed of float-point genetic algorithms, a new genetic operator named intergenerational differential crossover operator was proposed. The operator was applied to simulating parameter estimation of nonlinear system, and the resulted showed its validity and its superiority over a general crossover operator.