Aiming at features of the Markowitz mean-variance model and the weakness and shortage of simple Genetic Algorithm ( GA ) in the model, a kind of improved GA, namely dual mutation GA, is put forward. 针对马柯维茨均值-方差模型的特点和简单遗传算法(SGA)在求解该模型中所存在的缺点和不足,本文提出了一种改进的遗传算法-双变异遗传算法。
Improved K-Means Algorithm Based on a Simple Genetic Algorithm(SGA) 一种基于简单遗传算法(SGA)的K-Means改进算法
Aiming at the problem that the simple genetic algorithm is easy to produce premature convergence, an Adaptive Genetic Algorithm ( AGA ) is presented to automatically generate test data. 针对简单遗传算法(SGA)容易产生早熟收敛的问题,提出一种自适应遗传算法,用以自动生成测试数据。
In this paper, part parameters in8 steps of the RAGA are amended, and fine search is carried out with simple genetic algorithm ( SGA ) in the last reduced domain. 对实码加速遗传算法(RAGA)8个步骤的局部参数进行修改,再对最后一次加速收缩后的区间用标准遗传算法(SGA)进行精细搜索。
Different from Simple Genetic Algorithm(SGA) that adopts random mating strategy, mating operator mates chromosomes according to schema order and schema defining length. 配对算子不像简单遗传算法(SGA)那样随机选择配对,而是根据模式阶和模式长度对染色体进行配对。