错位交叉 meaning in Chinese
stagered junction
Examples
- In the next section of this paper we describe a non - generational ga for multiobjective optimization problems ( mop ) . in it the replacement policy is such that an offspring replaces the worst one in the current population only if it is better then it
在将错位交叉算子应用于多目标优化问题求解时，本文提出一种基于非群体迭代型的小生境多目标优化遗传算法，即算法迭代过程中不是更换种群全部或大部分个体，而是每次更新群体中最差的个体。 - In the same time we also use it to test the power of dc crossover . in this algorithm every element in the population a domination count is defined together with a neighborhood density measure based on a sharing function . those two parameters are then non - linear combined in order to define the individual ' s fitness
算法通过计算种群中pareto优于某个个体的个体数目以及个体所在位置的密集度来定义适应度函数，多个算例的测试结果表明该算法结合错位交叉算子具有较好的性能，能够使算法收敛到pareto概念下的比较均匀的一组非劣最优解。 - Dc has two attractive characteristics : ( 1 ) dc can make genes in a chromosome keep good diversity . dc overcomes the evil of traditional crossovers , which cause gas get into prematurity . ( 2 ) dc well reduces algorithms " generations by guiding them to search in global optimal ' s neighborhood space
通过对交叉算子产生新个体的机理以及实际问题的特征进行分析后，本文提出一种基于非等位基因交叉运算的错位交叉算子，该算子的主要优点在于： （ 1 ）能够使种群个体的基因值更加有效地保持多样性，克服传统交叉算子下算法易于陷入局部最优解的缺陷； （ 2 ）引导遗传算法在最优解邻域内搜索，从而提高算法的优化速度。