A Ranking Based Adaptive Evolutionary  Operator Genetic Algorithm

Song Aiguo

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A Ranking Based Adaptive Evolutionary Operator Genetic Algorithm

更新时间：2025-12-08

- A Ranking Based Adaptive Evolutionary Operator Genetic Algorithm
- Acta Electronica Sinica Issue 1, (1999)
- 作者机构：
  
  1. 东南大学仪器科学系
  2. 东南大学无线电系
  3. 东南大学仪器科学系东南大学无线电系
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP18
- Published：1999
- 稿件说明：
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[1]宋爱国,陆佶人.一种基于排序操作的进化算子自适应遗传算法[J].电子学报,1999(01):86-89.

Song Aiguo. A Ranking Based Adaptive Evolutionary Operator Genetic Algorithm[J]. Acta Electronica Sinica, 1999, (1).
[1]宋爱国,陆佶人.一种基于排序操作的进化算子自适应遗传算法[J].电子学报,1999(01):86-89. DOI：

Song Aiguo. A Ranking Based Adaptive Evolutionary Operator Genetic Algorithm[J]. Acta Electronica Sinica, 1999, (1). DOI：

摘要

提出了一种基于排序操作的进化算子自适应的遗传算法，该算法中，每个个体按适应值大小进行排序，个体的选择、交叉、变异算子的概率根据个体排序值来自适应地确定，其中选择概率还随进化过程而调节．利用Ｍａｒｋｏｖ链的分析法证明了该算法的全局收敛性．最后，实验结果表明该算法同传统的遗传算法相比不仅能收敛到全局最优解，而且具有较快的收敛速度．

Abstract

In this paper

a ranking based adaptive evolutionary operator genetic algorithm（RAOGA） is proposed.RAOGA uses ranking operator to rank the individuals according to their fitness value

and the probabilities of select operator

crossover operator

mutation operator are adapted to ranking value of the individual

in the meantime

the probability of select is adapted to evolving process.Then

we prove its performance of convergence to the global optimum by means of Markov chain analysis.At last

the experimental result shows that the RAOGA converges to the global optimum more rapidly than that of the conventional genetic algorithms.

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