吉林大学学报(工学版) ›› 2019, Vol. 49 ›› Issue (4): 1339-1344.doi: 10.13229/j.cnki.jdxbgxb20181268

• • 上一篇    

改进的鸡群优化算法

李宾1(),申国君2,孙庚2,3(),郑婷婷2   

  1. 1. 吉林大学 数学学院, 长春 130012
    2. 吉林大学 计算机科学与技术学院, 长春 130012
    3. 吉林大学 通信工程学院, 长春 130012
  • 收稿日期:2018-08-12 出版日期:2019-07-01 发布日期:2019-07-16
  • 通讯作者: 孙庚 E-mail:lb@jlu.edu.cn;sungeng@jlu.edu.cn
  • 作者简介:李宾(1960?),女,副教授. 研究方向:群智能优化算法分析与设计. E?mail:lb@jlu.edu.cn
  • 基金资助:
    国家自然科学基金项目(61872158);中国博士后科学基金项目(2018M640283)

Improved chicken swarm optimization algorithm

Bin LI1(),Guo⁃jun SHEN2,Geng SUN2,3(),Ting⁃ting ZHENG2   

  1. 1. College of Mathematics, Jilin University, Changchun 130012, China
    2. College of Computer Science and Technology, Jilin University, Changchun 130012, China
    3. College of Communication Engineering, Jilin University, Changchun 130012, China
  • Received:2018-08-12 Online:2019-07-01 Published:2019-07-16
  • Contact: Geng SUN E-mail:lb@jlu.edu.cn;sungeng@jlu.edu.cn

摘要:

针对鸡群优化算法中解的更新效率较低且缺乏探索性等问题,提出了一种改进的鸡群优化算法。该算法基于标准鸡群优化算法的种群分组更新机制,并借鉴狼群优化算法和粒子群优化算法的思想,引入改进因子和去重操作算子分别用以增强算法的寻优能力和提高种群的多样性。通过与其他4种算法在CEC 2014测试函数集上进行比较,结果表明本文算法在绝大多数测试函数上均表现出了良好的优化效果,在求解精度及收敛速度方面也优于其他算法。

关键词: 计算机应用, 鸡群优化算法, 收敛速度, 功能优化

Abstract:

Based on the hierarchy mechanism of the conventional chicken swarm optimization (CSO) algorithm, an improved chicken swarm optimization (ICSO) algorithm is proposed to enhance the solution accuracy and the convergence rate of the conventional CSO algorithm. The ICSO algorithm introduces several improved factors that learned from the grey wolf optimizer (GWO) and the particle swarm optimization (PSO), to extend the searching ability of the algorithm. Moreover, a duplicate remove operator is also introduced to improve the diversity of the population. Experimental results show that the accuracy of the solution and the convergence rate of the proposed algorithm are better than other benchmark algorithms.

Key words: computer applications, chicken swarm optimization(CSO) algorithm, convergence rate, function optimization

中图分类号: 

  • TP301

图1

ICSO算法流程图"

表1

基准函数测试结果"

函数ICSO算法FA算法CSO算法PSO算法BBO算法
最优总数21117179
f15.55e+04 ± 4.75e+041.78e+03 ± 1.12e+042.91e+06 ± 2.44e+062.18e+03 ± 1.93e+042.60e+05 ± 2.26e+06
f21.08e+03 ± 2.71e+022.96e+02 ± 2.23e+031.25e+07 ± 7.15e+071.26e+03 ± 4.20e+025.02E+03 ± 1.09e+05
f37.71e+02 + 2.86e+023.00e+02 ± 3.21e-041.45e+03 ± 6.71e+023.00e+02 ± 5.75e-031.01e+04 ± 3.39e+03
f44.00e+02 ± 1.88e-014.35e+02 ± 8.24e+004.41e+02 ± 8.99e+004.00e+02 ± 1.70e+014.35e+02 ±1.16e+01
f55.19e+02 ± 5.97e+005.20e+02 ± 2.80e+005.20e+02 ± 3.47e+005.20e+02 ± 5.48e+005.20e+02 ± 7.66e-02
f66.00e+02 ± 1.24e+006.00e+02 ± 2.23e-026.05e+02 ± 8.97e-016.00e+02 ± 9.31e-016.02e+02 ± 1.19e+00
f77.00e+02 ± 1.00e-027.00e+02 ± 4.89e-027.07e+02 ± 2.21e+007.00e+02 ± 3.53e-027.00e+02 ± 1.14e-01
f88.03e+02 ± 3.77e+008.11e+02 ± 3.07e+008.12e+02 ± 3.27e+008.00e+02 ± 1.61e-148.01e+02 ± 1.20e+00
f99.06e+02 ± 4.06e+009.07e+02 ± 3.23e+009.12e+02 ± 3.43e+009.07e+02 ± 1.71e+009.14e+02 ± 4.69e+00
f101.06e+03 ± 2.36e+021.24e+03 ± 1.68e+021.26e+03 ± 8.50e+011.13e+03 ± 6.20e+011.03e+03 ± 1.18e+01
f111.46e+03 ± 2.01e+021.69e+03 ± 1.68e+021.66e+03 ± 1.72e+021.48e+03 ± 1.29e+022.02e+03 ± 2.10e+02
f121.20e+03 ± 3.14e-021.20e+03 ± 6.00e-031.20e+03 ± 1.17e-011.20e+03 ± 5.62e-021.20e+03 ± 2.40e-01
f131.30e+03 ± 6.97e-021.30e+03 ± 1.91e-021.30e+03 ± 8.45e-021.30e+03 ± 4.53e-021.30e+03 ± 9.47e-02
f141.40e+03 ± 7.79e-021.40e+03 ± 3.86e-021.40e+03 ± 1.63e-011.40e+03 ± 2.26e-021.40e+03 ± 7.76e-02
f151.50e+03 ± 1.81e-011.50e+03 ± 1.48e-011.50e+03 ± 4.48e-011.50e+03 ± 2.38e-011.50e+03 ± 5.68e-01
f161.60e+03 ± 3.18e-011.60e+03 ± 4.33e-011.60e+03 ± 3.30e-011.60e+03 ± 5.77e-011.60e+03 ± 4.10e-01
f172.16e+03 ± 2.47e+022.45e+03 ± 3.62e+023.87e+03 ± 2.80e+033.89e+03 ± 1.23e+031.21e+04 ± 3.07e+05
f181.91e+03 ± 6.00e+016.54e+03 ± 3.13e+008.68e+03 ± 2.71e+032.43e+03 ± 3.90e+034.02e+03 ± 5.01e+04
f191.90e+03 ± 3.48e-011.90e+03 ± 6.41e-011.90e+03 ± 8.40e-011.90e+03 ± 6.95e-011.90e+03 ± 4.52e-01
f202.10e+03 ± 6.34e+012.02e+03 ± 2.25e+012.07e+03 ± 1.42e+032.01e+03 ± 2.09e+002.56e+04 ± 2.78e+04
f212.36e+03 ± 6.19e+002.55e+03 ± 2.10e+022.37e+03 ± 7.96e+022.22e+03 ± 5.13e+011.20e+04 ± 5.65e+04
f222.22e+03 ± 7.12e+012.22e+03 ± 5.66e+012.23e+03 ± 3.30e+012.20e+03 ± 1.00e+012.22e+03 ± 4.51e+01
f232.40e+03 ± 7.12e+012.63e+03 ± 1.26e-072.63e+03 ± 1.91e+012.63e+03 ± 1.02e-122.63e+03 ± 1.28e-01
f242.52e+03 ± 4.68e+002.52e+03 ± 4.87e+002.54e+03 ± 1.24e+012.51e+03 ± 4.04e+002.53e+03 ± 7.41e+00
f252.61e+03 ± 9.46e+002.62e+03 ± 1.79e+012.68e+03 ± 9.89e+002.70e+03 ± 3.72e+012.70e+03 ± 9.47e-02
f262.70e+03 ± 4.46e-022.70e+03 ± 1.62e-022.70e+03 ± 4.45e-022.70e+03 ± 4.31e-022.70e+03 ± 2.60e+01
f272.70e+03 ± 6.15e+013.00e+03 ± 1.37e+023.08e+03 ± 1.86e+023.10e+03 ± 1.67e+023.11e+03 ± 1.84e+02
f283.00e+03 ± 6.35e+013.16e+03 ± 1.43e+023.19e+03 ± 1.20e+013.19e+03 ± 7.26e+013.17e+03 ± 2.69e+01
f293.14e+03 ± 9.52e+013.33e+03 ± 2.41e+053.67e+03 ± 2.30e+023.23e+03 ±8.25e+053.57e+03 ± 5.15e+02
f303.47e+03 ± 6.87e+013.75e+03 ± 1.59e+023.92e+03 ± 3.03e+023.63e+03 ± 2.46e+023.65e+03 ± 2.59e+02

图2

各种算法在函数f5上的收敛曲线"

图3

各种算法在函数f16上的收敛曲线"

图4

各种算法在函数f27上的收敛曲线"

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