In the HGA , heuristic algorithm is used to produced initial population , self-adaptive parameter are used in copy operator, crossover operator and mutation operator .
混合遗传算法在产生初始种群时引入启发式方法,采用自适应遗传参数和交替使用两种交叉算子;
The algorithm makes fully use of initial value sensitivity and track ergodicity of chaos, overcoming the disadvantage of big searching dead zone existed in conventional chaotic mutation model.
该算法充分利用混沌的初值敏感性和轨道遍历性,克服了已有混沌变异模型存在搜索盲区大的缺点。
A new crossover and mutation operation suitable for the matrix code is developed, and they can ensure that the new initial chromosomes are always feasible.
针对矩阵编码提出的特殊交叉算子和变异算子,能保证生成的新个体总是有效的。
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