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Zhenwu Wang, Chengfeng Yin. Chicken Swarm Optimization Algorithm Based on Behavior Feedback and Logic Reversal[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2018, 27(3): 348-356. doi: 10.15918/j.jbit1004-0579.17177
Citation: Zhenwu Wang, Chengfeng Yin. Chicken Swarm Optimization Algorithm Based on Behavior Feedback and Logic Reversal[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2018, 27(3): 348-356.doi:10.15918/j.jbit1004-0579.17177
shu

Chicken Swarm Optimization Algorithm Based on Behavior Feedback and Logic Reversal

doi:10.15918/j.jbit1004-0579.17177

  • Department of Computer Science and Technology, China University of Mining and Technology, Beijing 100083, China

  • Received Date:2017-11-28
    Abstract
  • Considering the problem that a rooster in chicken swarm optimization (CSO) easily falls into a local optimum and cannot fully demonstrate the population wisdom, the paper proposed an improved CSO algorithm, which based on behavior feedback from hens to rooster and rooster behavior logic reversal, therefore it is named behavior feedback and logic reversal CSO (BFLRCSO). The proposed algorithm changes the original rooster behavior logic to boost the convergence rate, which can accelerate the rooster optimization process, and the algorithm also introduces a feedback mechanism from hens to rooster which can prevent swarm dropping into a local optimum. The experiment results demonstrated that the BFLRCSO algorithm is not easy to fall into a local optimum, which has a better optimization result and shorter optimization time compared with the original CSO algorithm in both high and low dimensional search space.
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    • References (19)
  • [1]
    Holland J H. Adaptation in natural and artificial systems[J]. Quarterly Review of Biology,1975,6(2):126-137.
    [2]
    Kennedy J, Eberhart R C. Particle swarm optimization[C]//Proceedings of the 1995 IEEE International Conference on Neural Networks. Perth, Australia:IEEE Service Centre, 1995:1942-1948.
    [3]
    Karaboga D, Gorkemli B, Ozturk C, et al. A comprehensive survey:artificial bee colony (ABC) algorithm and applications[J]. Artificial Intelligence Review, 2014, 42(1):21-57.
    [4]
    Li Xiaolei, Shao Zhijiang, Qian Jixin. An optimizing method based on autonomous animats:fish-swarm algorithm[J]. Systems Engineering-Theory & Practice, 2002, 22(11):32-38.
    [5]
    Yang X S.A new metaheuristic bat-inspired algorithm[J]. Computer Knowledge & Technology, 2010, 284:65-74.
    [6]
    Meng X, Liu Y, Gao X, et al. A new bio-inspired algorithm:chicken swarm optimization[M]//Advances in Swarm Intelligence. New York:Springer International Publishing, 2014:86-94.
    [7]
    Kong Fei, Wu Dinghui. An improved chicken swarm optimization algorithm[J].Journal of Jiangnan University(Natural Science Editon), 2015, 14(6):681-688. (in Chinese)
    [8]
    Chen Y L, He P L, Zhang Y H. Combining penalty function with modified chicken swarm optimization for constrained optimization[C]//International Conference on Information Sciences, Machinery, Materials and Energy, 2015:1899-1907.
    [9]
    Qu Chiwen,Zhao Shi'an,Fu Yanming.Chicken swarm optimization based on elite opposition-based learning[J].Mathematical Problems in Engineering,2017(11):1-20.
    [10]
    Wu Dinghui,Xu Shipeng,Kong Fei.Convergence analysis and improvement of the chicken swarm optimization algorithm[J].IEEE ACCESS,2016,4:9400-9412.
    [11]
    Liang Shuang,Feng Tie,Sun Geng.Sidelobe-level suppression for linear and circular antenna arrays via the cuckoo search-chicken swarm optimization algorithm[J].IET Microwaves Antennas & Propagation,2017,11(2):209-218.
    [12]
    Feng Tiana,Rong Zhanga,Lewandowskic Jacek.Deadlock-free migration for virtual machine consolidation using Chicken Swarm Optimization algorithm[J].Journal of Intelligent & Fuzzy Systems,2017,32(2):1389-1400.
    [13]
    Chen Shaolong,Yang Renyu,Yang Renhuan.A parameter estimation method for nonlinear systems based on improved boundary chicken swarm optimization[J].Discrete Dynamics in Nature and Society,2016,2016:1-12.
    [14]
    Hafez A I, Zawbaa H M, Emary E, et al. An innovative approach for feature selection based on chicken swarm optimization[C]//International Conference on Soft Computing and Pattern Recognition, IEEE, 2015:19-24.
    [15]
    Banerjee Subhabrata, Chattopadhyay Sudipta. Improved serially concatenated convolution turbo code (SCCTC) using chicken swarm optimization[C]//IEEE Power, Communication and Information Technology Conference, 2015:1-6.
    [16]
    Chen Peng, Mao Yongyi. Wireless sensor network node localization algorithm based on chicken swarm optimization and multi-power mobile anchor[C]//3rd International Conference on Materials Engineering, Manufacturing Technology and Control,2016:245-250.
    [17]
    Khaled Ahmed, Hassanien Aboul Ella, Ezzat Ehab, et al. An adaptive approach for community detection based on chicken swarm optimization algorithm[J].Advances in Intelligent Systems and Coumputing,2017,536:281-288.
    [18]
    Li Yongtao,Wu Yu,Qu Xiangju.Chicken swarm-based method for ascent trajectory optimization of hypersonic vehicles[J].Journal of Aerospace Engineering,2017,30(5):1-12.
    [19]
    Nursyiva Irsalinda, Yanto Iwan Tri Riyadi,Chiroma Haruna,et al.A framework of clustering based on chicken swarm optimization[C]//The 2 ndInternational Conference on Soft Computing and Data Mining,2017,549:336-343.
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