[1]叶亚荣,贺兴时,张超.基于随机扰动的自适应布谷鸟算法[J].计算机技术与发展,2019,29(05):77-80.[doi:10. 3969 / j. issn. 1673-629X. 2019. 05. 017]
　YE Ya-rong,HE Xing-shi,ZHANG Chao.An Adaptive Cuckoo Algorithm Based on Random Disturbance[J].,2019,29(05):77-80.[doi:10. 3969 / j. issn. 1673-629X. 2019. 05. 017]
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基于随机扰动的自适应布谷鸟算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
29
期数:
2019年05期
页码:
77-80
栏目:
智能、算法、系统工程
出版日期:
2019-05-10

文章信息/Info

Title:
An Adaptive Cuckoo Algorithm Based on Random Disturbance
文章编号:
1673-629X(2019)05-0077-04
作者:
叶亚荣; 贺兴时; 张超
西安工程大学 理学院,陕西 西安 710048
Author(s):
YE Ya-rong; HE Xing-shi; ZHANG Chao
School of Science,Xi’an Polytechnic University,Xi’an 710048,China
关键词:
布谷鸟算法; 自适应步长; 鸟窝位置; 随机扰动
Keywords:
cuckoo algorithm; adaptive step size; nest location; random disturbance
分类号:
TP301. 6
DOI:
10. 3969 / j. issn. 1673-629X. 2019. 05. 017
摘要:
布谷鸟搜索算法(CS)是模仿布谷鸟的繁殖行为所建的一种元启发式算法。 这是一种新兴启发算法,通过模拟某些种属布谷鸟的寄生育雏崽来有效地求解最优化问题。 针对该算法计算精度不高,收敛速度慢,容易陷入局部最优等缺陷,提出了一种基于自适应步长随机扰动的布谷鸟搜索算法(ASCS)。 在增加鸟窝位置变化活力的基础上,对鸟窝位置之间的距离引入自适应的调整步长因子,可以防止算法在运行过程中陷入局部最优。 同时为了更大程度地提高鸟窝的计算精度与搜索速度,在寻找最优鸟窝的时候增加一个扰动因子,提高了算法的收敛速度。 通过 7 个测试函数进行仿真实验,结果证明了该算法的可行性,其性能显著优于原始的布谷鸟算法。
Abstract:
The cuckoo search (CS) is a kind of meta-heuristic algorithm constructed by imitating the breeding behavior of cuckoos. This is an emerging heuristic algorithm that effectively solves optimization problems by simulating the breeding of some species of cuckoos.Aiming at the shortcomings of this algorithm,such as low computational accuracy,slow convergence speed and easy to be trapped in localoptimum,we propose a cuckoo search based on adaptive step size random perturbation (ASCS). On the basis of increasing the vitality ofthe bird nest position, an adaptive adjustment step factor is introduced to the distance between the bird nest positions to prevent thealgorithm from falling into a local optimum during the operation. At the same time,in order to improve the calculation accuracy andsearch speed of the bird nest to a greater extent, an interference factor is added to find the optimal bird nest, which improves theconvergence speed of the algorithm. The simulations are performed by seven test functions. The experiment shows that the ASCS isfeasible and its performance is significantly better than that of CS.

相似文献/References:

[1]江浩,阮奇. 基于变尺度法和自适应步长的布谷鸟搜索算法[J].计算机技术与发展,2015,25(10):38.
　JIANG Hao,RUAN Qi. A Cuckoo Search Algorithm Based on Variable Metric Method and Adaptive Step[J].,2015,25(05):38.
[2]方 涛,刘 涛,李 龙.基于自适应步长 FOA-SVM 算法的卡泵故障诊断[J].计算机技术与发展,2021,31(04):153.[doi:10. 3969 / j. issn. 1673-629X. 2021. 04. 026]
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更新日期/Last Update: 2019-05-10