摘要： 提出一种改进的遗传算法,即器官遗传算法。该算法改变经典的遗传算法在选择操作中对群体中被选中的个体的各个分量全部继承的做法,对各个分量按其所在个体的适应度分别进行选择和实行交叉、变异等操作然后将这些分量组成新一代个体。以非线性规划问题为例进行的实验结果表明该方法比使用经典的遗传算法具有更好的收敛速度。

关键词: 遗传算法, 优化, 遗传操作

Abstract: A new type of genetic algorithm i.e. organ genetic algorithm is presented. Unlike the traditional genetic algorithm in whichthe selection operations adopt all the components of the individuals selected, this algorithm selects each component according to the value of the fitness function of the individual it belongs to, operations of crossover and mutation are also made on these selected values of each component. Then these components are combined to form the individuals of the new generation. Experimental results on the problem of nonlinear programming show that this method has much higher convergence speed than that of traditional GA.

中图分类号: 

• TP301.6