Cuckoo search algorithm based on differential evolution

doi:10.11772/j.issn.1001-9081.2014.06.1631

Journal of Computer Applications ›› 2014, Vol. 34 ›› Issue (6): 1631-1635.DOI: 10.11772/j.issn.1001-9081.2014.06.1631

• Artificial intelligence • Previous Articles Next Articles

Cuckoo search algorithm based on differential evolution

XIAO Huihui,DUAN Yanming

College of Computer and Information Engineering, Hechi University, Yizhou Guangxi 546300, China

Received:2013-12-25 Revised:2014-02-16 Online:2014-07-02 Published:2014-06-01
Contact: DUAN Yanming

基于差分进化的布谷鸟搜索算法

肖辉辉,段艳明

河池学院计算机与信息工程学院,广西宜州 546300

通讯作者: 段艳明
作者简介:肖辉辉(1977-),男,江西吉安人,讲师,硕士,主要研究方向:智能计算、数据库优化;段艳明(1978-),女,江西吉安人,讲师,硕士,主要研究方向:智能计算。
基金资助:
国家自然科学基金资助项目;广西教育厅科研基金资助项目

Abstract

Abstract:

In order to solve the problems of Cuckoo Search (CS) algorithm including low optimizing accuracy and weak local search ability, an improved CS algorithm with differential evolution strategy was presented. The individual variation was completed in the algorithm before population with two weighted differences increased on its individuals entering the next iteration, then crossover operation and select operation were performed to obtain optimal individual, which making the CS algorithm lack of mutation mechanism have the variation mechanism, so as to increase the diversity of the CS algorithm, avoid individual species into local optimum and enhance the global optimization ability. The algorithm was put through several classical test functions and a typical application example. The simulation results show that the new algorithm has better global searching ability, and the convergence precision, convergence speed and optimization success rate are significantly better than those of the basic CS algorithm.

摘要：

针对基本布谷鸟搜索算法局部搜索能力弱、寻优精度低等不足,提出了一种具有差分进化策略的改进布谷鸟搜索算法。该算法是在种群进入下一次迭代之前在其个体上增加两个带权的差来实现个体变异,再对其进行交叉、选择操作得到最优个体,使缺乏变异机制的布谷鸟搜索算法具有变异能力,从而提高布谷鸟搜索算法的多样性,避免种群个体陷入局部最优,增强算法全局寻优能力。对几种经典测试函数和1个典型应用实例进行测试,仿真实验结果表明,新算法具有更好的全局搜索能力,在收敛精度、收敛速度以及寻优成功率等性能上显著优于基本布谷鸟搜索算法。

CLC Number:

TP301.6

XIAO Huihui DUAN Yanming. Cuckoo search algorithm based on differential evolution[J]. Journal of Computer Applications, 2014, 34(6): 1631-1635.

肖辉辉段艳明. 基于差分进化的布谷鸟搜索算法[J]. 计算机应用, 2014, 34(6): 1631-1635.

References

[1]ZHUANG L, JING F, ZHU X Y. Movie review mining and summarization[C]// Proceedings of the 15th ACM International Conference on Information and Knowledge Management. New York: ACM Press, 2006: 43-50.
[2]Di FABBRIZIO G, GUPTA N, BESANA S, et al. Have2eat: a restaurant finder with review summarization for mobile phones[C]// COLING 2010: Proceedings of the 23rd International Conference on Computational Linguistics: Demonstrations. New York: ACM Press, 2010: 17-20.
[3]ZHU J, ZHU M, WANG H, et al. Aspect-based sentence segmentation for sentiment summarization[C]// Proceedings of the 1st International CIKM Workshop on Topic-Sentiment Analysis for Mass Opinion. New York: ACM Press, 2009: 65-72.
[4]BEINEKE P, HASTIE T, MANNING C, et al. Exploring sentiment summarization[EB/OL].[2013-10-10]. http://ia-1c-2010.googlecode.com/svn/trunk/TP%20Final/Papers/leer-%20Tomates%20SS04-07-003.pdf.
[5]CHANG Y L,CHIEN J T. Latent Dirichlet learning for document summarization[C]// ICASSP 2009: Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing. Piscataway: IEEE Press, 2009: 1689-1692.
[6]CELIKYILMAZ A, HAKKAN-TUR D. A hybrid hierarchical model for multi-document summarization[C]// ACL 2010: Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics. Stroudsburg: Association for Computational Linguistics, 2010: 815-824.
[7]YANG X, MA J, YANG T, et al. Automatic mult-idocument summarization based on the latent Dirichlet topic allocation model [J]. CAAI Transactions on Intelligent Systems,2010,5(2): 169-176.(杨潇,马军,杨同峰,等.主题模型 LDA 的多文档自动文摘[J].智能系统学报,2010,5(2): 169-176.)
[8]ZHU Y, MIN J, ZHOU Y, et al. Semantic orientation computing based on HowNet[J]. Journal of Chinese Information Processing, 2006, 20(1): 14-20.(朱嫣岚,闵锦,周雅倩,等.基于HowNet的词汇语义倾向计算[J].中文信息学报, 2006, 20(1): 14-20.)
[9]XU L, LIN H, YANG Z. Text orientation identification based on semantic comprehension[J]. Journal of Chinese Information Processing, 2007, 21(1): 96-100.(徐琳宏,林鸿飞,杨志豪.基于语义理解的文本倾向性识别机制[J].中文信息学报,2007, 21(1): 96-100.)
[10]BLEI D M, NG A Y, JORDAN M I. Latent Dirichlet allocation [J]. The Journal of Machine Learning Research, 2003,3: 993-1022.
[11]JIANG C, PENG H, CHEN J, et al. Automatic abstract based on the characteristics of keywords weight and sentences term [J]. Journal of South China University of Technology: Natural Science, 2010,38(7): 50-55.(蒋昌金,彭宏,陈建超,等.基于主题词权重和句子特征的自动文摘[J].华南理工大学学报: 自然科学版, 2010,38(7): 50-55.)
[12]STEYVERS M, GRIFFITHS T. Probabilistic topic models[J]. Handbook of Latent Semantic Analysis, 2007, 427(7): 424-440.
[13]ZHANG D. Research on key problems in text sentiment classification and opinion summarization[D]. Jinan: Shandong University,2012.(张冬梅.文本情感分类及观点摘要关键问题研究[D].济南:山东大学,2012.)

[1]	. YOLOv5s-MRD: an efficient fire and smoke detection algorithm for complex scenarios based on YOLOv5s [J]. Journal of Computer Applications, 0, (): 0-0.
[2]	Qiye ZHANG, Xinrui ZENG. Efficient active-set method for support vector data description problem with Gaussian kernel [J]. Journal of Computer Applications, 2024, 44(12): 3808-3814.
[3]	. Path planning of multi-UAV formation based on improved artificial potential field method [J]. Journal of Computer Applications, 0, (): 0-0.
[4]	. Dual-population dual-stage evolutionary algorithm for complex constrained multi-objective optimization problems [J]. Journal of Computer Applications, 0, (): 0-0.
[5]	Qin LENG, Zhengyuan MAO. Two echelon location-routing optimization considering facility sizing decision [J]. Journal of Computer Applications, 2024, 44(11): 3513-3520.
[6]	Qingyuan PENG, Xiaofeng WANG, Junxia WANG, Yingying HUA, Ao TANG, Fei HE. Review of phase transition in satisfiability problems [J]. Journal of Computer Applications, 2024, 44(11): 3503-3512.
[7]	Renke SUN, Zhiyu HUANGFU, Hu CHEN, Zhongnian LI, Xinzheng XU. Survey of neural architecture search [J]. Journal of Computer Applications, 2024, 44(10): 2983-2994.
[8]	Antai SUN, Ye LIU, Dongmei XU. Dynamic surface asymptotic compensation algorithm for multi-agent systems [J]. Journal of Computer Applications, 2024, 44(10): 3151-3157.
[9]	Chaoying YAN, Ziyi ZHANG, Yingnan QU, Qiuyu LI, Dixiang ZHENG, Lijun SUN. Double auction carbon trading based on consortium blockchain [J]. Journal of Computer Applications, 2024, 44(10): 3240-3245.
[10]	. Dung beetle optimizer algorithm with restricted reverse learning and Cauchy-Gauss variation [J]. Journal of Computer Applications, 0, (): 0-0.
[11]	Guanglei YAO, Juxia XIONG, Guowu YANG. Flower pollination algorithm based on neural network optimization [J]. Journal of Computer Applications, 2024, 44(9): 2829-2837.
[12]	Shanglong LI, Jianhua LIU, Heming JIA. Reptile search algorithm based on multi-hunting coordination strategy [J]. Journal of Computer Applications, 2024, 44(9): 2818-2828.
[13]	Yan LI, Dazhi PAN, Siqing ZHENG. Improved adaptive large neighborhood search algorithm for multi-depot vehicle routing problem with time window [J]. Journal of Computer Applications, 2024, 44(6): 1897-1904.
[14]	. Robust shapeles representation method for time series [J]. Journal of Computer Applications, 0, (): 0-0.
[15]	HU Linbo , NI Zhiwei , CHENG Jiale, LIU Wentao , ZHU Xuhui , . Complex collaborative crowdsourcing task allocation method based on fusion community detection [J]. Journal of Computer Applications, 0, (): 0-0.

Cuckoo search algorithm based on differential evolution

基于差分进化的布谷鸟搜索算法

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics