| 本文已被：浏览 4200次 下载 5539次 |
码上扫一扫！ |
|
|
| 演化算法时间复杂性的趋势条件 |
|
何军1, 姚新1, 康立山2
|
|
1.伯明翰大学计算机学院,伯明翰,B15,2TT,英国;2.武汉大学软件工程国家重点实验室,湖北,武汉,430072
|
|
| 摘要: |
| 计算时间复杂性是演化理论中的一个重大课题.将趋势分析引入演化算法的平均时间复杂性分析,可用于很广一类演化算法及许多问题.基于趋势分析,研究了确定演化算法时间复杂性的一些有用的趋势条件.这些条件应用于完全欺骗问题以验证其有效性. |
| 关键词: 演华算法 时间复杂性 Markov链 组合优化 |
| DOI： |
| 分类号: |
| 基金项目:Supported by the National Natural Science Foundation of China under Grant Nos. 60133010, 60073043 and 70071042 (国家自然科学基金);the Research Foundation of the State Key Laboratory of Software Engineering at Wuhan University of China (武汉大学软件工程国） |
|
| Drift Conditions for Time Complexity of Evolutionary Algorithms |
|
HE Jun,YAO Xin,KANG Li-shan
|
| Abstract: |
| The computational time complexity is an important topic in the theory of evolutionary algorithms. This paper introduces drift analysis into analysing the average time complexity of evolutionary algorithms, which are applicable to a wide range of evolutionary algorithms and many problems. Based on the drift analysis, some useful drift conditions to determine the time complexity of evolutionary algorithms are studied. These conditions are applied into the fully deceptive problem to verify their efficiency. |
| Key words: evolutionary algorithms time complexity Markov chain combinatorial optimisation |
