Using a set of elite individuals in a genetic algorithm

机译：在遗传算法中使用一组精英个体

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A new method of selection of individuals for crossover is presented and tested. Its main idea is that one of the selected individuals is always a member of an "elite" group, consisting of n best individuals currently in the population. This method does not slow down the execution of the algorithm and shows a marked improvement in search results.

机译：提出和测试了一种新的单个交叉选择方法。其主要思想是其中一个选定的人始终是“精英”组的成员，由目前人口中的N个最佳人士组成。该方法不会减慢算法的执行，并显示搜索结果的显着改进。

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《Information Technology Interfaces, 2004. 26th International Conference on》|2004年|p.531-535|共5页
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Musnjak M.; Golub M.;
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正文语种
中图分类无线电电子学、电信技术;
关键词
genetic algorithms; processor scheduling; search problems; genetic algorithm; elite group; multiprocessor scheduling;

机译：遗传算法处理器调度搜索问题遗传算法精英群多处理器调度;

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专利

1. Elite genetic algorithms with adaptive mutations for solving continuous optimization problems - application to modeling of the optical constants of solids [J] . Aleksandra B. Djurisic Optics Communications: A Journal Devoted to the Rapid Publication of Short Contributions in the Field of Optics and Interaction of Light with Matter . 1998,第1a3期

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2. A hybrid method of set reduction algorithm and modified genetic algorithm for set covering problem [J] . XiangYang Chen Energy education science and technology . 2015,第2期

机译：一种混合方法对集合覆盖问题的缩减算法和修改遗传算法
3. Improved Wolf Pack Algorithm Based on Differential Evolution Elite Set [J] . Xiayang CHEN, Chaojing TANG, Jian WANG, IEICE transactions on information and systems . 2018,第7期

机译：基于差分进化精英集的改进Wolf Pack算法
4. Using a set of elite individuals in a genetic algorithm [C] . Musnjak M., Golub M. International Conference on Information Technology Interfaces . 2004

机译：在遗传算法中使用一组精英个体
5. PWiseGen: A genetic algorithms-based framework for pairwise test set generation. [D] . Flores, Pedro. 2010

机译：PWiseGen：基于遗传算法的成对测试集生成框架。
6. How many marker loci are necessary? Analysis of dominant marker data sets using two popular population genetic algorithms [O] . Michael F Nelson, Neil O Anderson 2013

机译：需要多少个标记基因座？使用两种流行的群体遗传算法分析显性标记数据集
7. Elite-initial population for efficient topology optimization using multi-objective genetic algorithms [O] . Hyunjin Shin, Akira Todoroki, Yoshiyasu Hirano 2013

机译：使用多目标遗传算法有效拓扑优化的精英 - 初始群体

Using a set of elite individuals in a genetic algorithm

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