正态随机噪声环境下遗传算法的动态适应度评价

doi:10.3969/j.issn.0372-2112.2019.03.019

电子学报 ›› 2019, Vol. 47 ›› Issue (3): 649-656.DOI: 10.3969/j.issn.0372-2112.2019.03.019

正态随机噪声环境下遗传算法的动态适应度评价

李军华, 黎明, 陈昊, 伍家驹

南昌航空大学江西省图像处理与模式识别重点实验室, 江西南昌 330063

收稿日期:2018-02-01 修回日期:2018-05-10 出版日期:2019-03-25
- 作者简介:
- 李军华 男,1974年生于江西莲花,教授,主要研究方向为进化计算、智能信息处理.E-mail:jhlee126@126.com;黎明男,1965年生于江西南昌,教授,博士生导师,主要研究方向为进化计算、图像处理;陈昊男,1982年生于山东平度,副教授,主要研究方向为智能进化算法及应用,模式识别与人工智能;伍家驹 男,1951年生于江西南昌,教授,主要研究方向为电子变压器电感器优化设计的可视化算法.
- 基金资助:
- 国家自然科学基金 (No.61440049，No.61866025）; 江西省自然科学基金 (No.20161BAB202038，No.20181BCB24008）

Dynamic Fitness Evaluation of Genetic Algorithms in Normal Random Noisy Environments

LI Jun-hua, LI Ming, CHEN Hao, WU Jia-ju

Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition, Nanchang Hangkong University, Nanchang, Jiangxi 330063, China

Received:2018-02-01 Revised:2018-05-10 Online:2019-03-25 Published:2019-03-25
- Supported by:
- National Natural Science Foundation of China (No.61440049, No.61866025); Natural Science Foundation of Jiangxi Province, China (No.20161BAB202038, No.20181BCB24008)

摘要/Abstract

摘要： 在大量实际应用问题进化优化的适应度评价都受到了噪声的干扰.本文研究了正态随机噪声对适应度评价的影响机理，对比分析了正态随机噪声环境下不同适应度评价方法的性能.本文提出了一种多次评价一次采样的动态适应度评价方法，该方法在种群更新过程中，重新评价上一代种群，可以降低伪优个体（劣个体）的生存周期，抑制随机噪声对优胜劣汰机制的影响.实验结果也表明总采样次数相同的情况下，新方法的性能优于一次评价一次采样和一次评价多次采样方法.

关键词: 遗传算法, 噪声环境, 适应度评价

Abstract: In many practical applications of evolutionary optimization,the fitness evaluation is subject to noise.In this paper,the effect of normal random noise on fitness evaluation is studied,and the performance of different fitness evaluation methods is compared and analyzed.A dynamic fitness evaluation method is proposed.In the process of population regeneration,the method evaluates all surviving individuals again,reduces the survival period of the pseudo-superior individuals (the inferior individuals),and restrains the interference with noise on the survival of the fittest.Experimental results show that the proposed method has better performance than the method of one evaluate and one sampling or one evaluate and multiple sampling at the same total number of sampling.

Key words: genetic algorithm, noisy environment, fitness evaluation

中图分类号:

TP301.6

李军华, 黎明, 陈昊, 等. 正态随机噪声环境下遗传算法的动态适应度评价[J]. 电子学报, 2019, 47(3): 649-656.

LI Jun-hua, LI Ming, CHEN Hao, et al. Dynamic Fitness Evaluation of Genetic Algorithms in Normal Random Noisy Environments[J]. Acta Electronica Sinica, 2019, 47(3): 649-656.

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正态随机噪声环境下遗传算法的动态适应度评价

Dynamic Fitness Evaluation of Genetic Algorithms in Normal Random Noisy Environments

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