2.845

2023影响因子

(CJCR)

  • 中文核心
  • EI
  • 中国科技核心
  • Scopus
  • CSCD
  • 英国科学文摘

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

一种新的启发式优化算法——五行环优化算法研究与分析

刘漫丹

刘漫丹. 一种新的启发式优化算法——五行环优化算法研究与分析. 自动化学报, 2020, 46(5): 957-970. doi: 10.16383/j.aas.c170657
引用本文: 刘漫丹. 一种新的启发式优化算法——五行环优化算法研究与分析. 自动化学报, 2020, 46(5): 957-970. doi: 10.16383/j.aas.c170657
LIU Man-Dan. Research and Analysis of a Novel Heuristic Algorithm: Five-elements Cycle Optimization Algorithm. ACTA AUTOMATICA SINICA, 2020, 46(5): 957-970. doi: 10.16383/j.aas.c170657
Citation: LIU Man-Dan. Research and Analysis of a Novel Heuristic Algorithm: Five-elements Cycle Optimization Algorithm. ACTA AUTOMATICA SINICA, 2020, 46(5): 957-970. doi: 10.16383/j.aas.c170657

一种新的启发式优化算法——五行环优化算法研究与分析

doi: 10.16383/j.aas.c170657
详细信息
    作者简介:

    刘漫丹  华东理工大学信息科学与工程学院自动化系教授. 2000年获得浙江大学控制理论与控制工程博士学位.主要研究方向为工业过程建模与优化, 智能优化算法及其应用. E-mail: liumandan@ecust.edu.cn

Research and Analysis of a Novel Heuristic Algorithm: Five-elements Cycle Optimization Algorithm

More Information
    Author Bio:

    LIU Man-Dan Professor in the Department of Automation, School of Information Science and Engineering, East China University of Science and Technology. She received her Ph. D. degree in control theory and control engineering from Zhejiang University, in 2000. Her research interest covers process modeling and optimization, intelligent optimization algorithms and applications

  • 摘要: 借鉴中国古代哲学理论所描述的系统动态平衡方法, 提出了解决连续函数优化问题的五行环优化算法.首先, 分析了基于五行元素生克原理而建立的五行环模型, 并在该模型基础上, 构建了元素空间结构以及元素更新方法等关键环节, 从而实现了五行环优化算法.随后, 对五行环优化算法进行了性能分析和关键参数比较, 针对标准测试函数, 将五行环优化算法与其他17个机制各异的启发式优化算法进行了比较, 实验结果验证了五行环优化算法的有效性和通用性, 也表明了其在求解连续函数优化问题上具有较好的优化性能.
    Recommended by Associate Editor QIAO Jun-Fei
    1)  本文责任编委 乔俊飞
  • 图  1  五行元素的相生相克关系

    Fig.  1  The generating and restricting interactions among five elements

    图  2  当$w_{gp}=w_{rp}=w_{ga}=w_{ra}=1$, $L=5$时, $m_i(k)$和$F_i(k)$的变化曲线

    Fig.  2  The changing curves of $m_i(k)$, $F_i(k)$ when $w_{gp}= w_{rp}=w_{ga}=w_{ra}=1$, $L=5$

    图  3  当$w_{gp}, w_{rp}, w_{ga}, w_{ra}$为(0, 1]区间上的随机数, $L=5$时, $m_i(k)$和$F_i(k)$的变化曲线

    Fig.  3  The changing curves of $m_i(k)$, $F_i(k)$ when $w_{gp}$, $w_{rp}$, $w_{ga}$, $w_{ra}$ is random numerical value in (0, 1] and $L=5$

    图  4  元素质量$m_i(k)$ ($i=1, 2, \cdots, 20$)分别在第1、50、300、1 000代时的变化情况

    Fig.  4  The changing of $m_i(k)$ ($i=1, 2, \cdots, 20$) at 1st, 50th, 300th, and 1 000th iterations

    图  5  FECO算法流程图

    Fig.  5  The flowchart of FECO algorithm

    图  6  在不同迭代次数时的元素$x_{ij}(k)$的分布情况以及最小$f(x_{ij}(k))$的变化曲线

    Fig.  6  The distribution of $x_{ij}(k)$ at various iterations and the changing curve of minimum $f(x_{ij}(k))$

    表  1  用Friedman检验法(显著性水平0.05)比较参数$L$和$q$

    Table  1  Comparison of $L$ and $q$ with Friedman test (significance value 0.05)

    Function $L=5/q=20$ $L=10/q=10$ $L=20/q=5$ $L=50/q=2$ $L=100/q=1$
    $f_1$ 3.22$\, \times\, 10^{-23}$ 7.65$\, \times\, 10^{-25}$ 1.64$\, \times\, 10^{-27}$ 3.65$\, \times\, 10^{-18}$ 1.99$\, \times\, 10^{3}$
    $f_2$ 3.18$\, \times\, 10^{-16}$ 9.35$\, \times\, 10^{-18}$ 3.35$\, \times\, 10^{-20}$ 9.80$\, \times\, 10^{-1}$ 2.88$\, \times\, 10^{1}$
    $f_3$ 1.47$\, \times\, 10^{2}$ 6.88$\, \times\, 10^{2}$ 1.35$\, \times\, 10^{3}$ 2.62$\, \times\, 10^{3}$ 1.22$\, \times\, 10^{4}$
    $f_4$ 4.22$\, \times\, 10^{-1}$ 1.47$\, \times\, 10^{0}$ 3.07$\, \times\, 10^{0}$ 1.13$\, \times\, 10^{1}$ 4.67$\, \times\, 10^{1}$
    $f_5$ 5.29$\, \times\, 10^{1}$ 5.59$\, \times\, 10^{1}$ 1.83$\, \times\, 10^{3}$ 1.39$\, \times\, 10^{2}$ 1.15$\, \times\, 10^{6}$
    $f_6$ 0.00$\, \times\, 10^{0}$ 0.00$\, \times\, 10^{0}$ 1.37$\, \times\, 10^{-1}$ 1.11$\, \times\, 10^{2}$ 4.61$\, \times\, 10^{3 }$
    $f_7$ 1.27$\, \times\, 10^{-2}$ 8.45$\, \times\, 10^{-3}$ 7.29$\, \times\, 10^{-3}$ 2.03$\, \times\, 10^{-2}$ 2.56$\, \times\, 10^{0}$
    $f_8$ $-$1.15$\, \times\, 10^{4}$ $-$1.14$\, \times\, 10^{4}$ $-$1.10$\, \times\, 10^{4}$ $-$9.85$\, \times\, 10^{3}$ $-$7.97$\, \times\, 10^{3}$
    $f_9$ 1.23$\, \times\, 10^{1}$ 1.31$\, \times\, 10^{1}$ 1.94$\, \times\, 10^{1}$ 5.79$\, \times\, 10^{1}$ 1.48$\, \times\, 10^{2 }$
    $f_{10}$ 1.53$\, \times\, 10^{-12}$ 2.22$\, \times\, 10^{-13}$ 1.70$\, \times\, 10^{-1}$ 3.60$\, \times\, 10^{0}$ 1.42$\, \times\, 10^{1 }$
    $f_{11}$ 6.10$\, \times\, 10^{-4}$ 1.24$\, \times\, 10^{-3}$ 4.34$\, \times\, 10^{-3}$ 1.17$\, \times\, 10^{-1}$ 1.80$\, \times\, 10^{1 }$
    $f_{12}$ 4.07$\, \times\, 10^{-3}$ 2.64$\, \times\, 10^{-2}$ 7.53$\, \times\, 10^{-2}$ 4.58$\, \times\, 10^{-1}$ 5.21$\, \times\, 10^{5}$
    $f_{13}$ 5.95$\, \times\, 10^{-2}$ 6.66$\, \times\, 10^{-1}$ 2.21$\, \times\, 10^{0}$ 1.32$\, \times\, 10^{1}$ 1.99$\, \times\, 10^{6 }$
    $f_{14}$ 1.02$\, \times\, 10^{0}$ 1.06$\, \times\, 10^{0}$ 1.14$\, \times\, 10^{0}$ 1.37$\, \times\, 10^{0}$ 2.50$\, \times\, 10^{0 }$
    $f_{15}$ 5.65$\, \times\, 10^{-4}$ 5.94$\, \times\, 10^{-4}$ 6.19$\, \times\, 10^{-4}$ 7.18$\, \times\, 10^{-4}$ 1.22$\, \times\, 10^{-3 }$
    $f_{16}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0 }$
    $f_{17}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$
    $f_{18}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0 }$
    $f_{19}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$
    $f_{20}$ $-$3.30$\, \times\, 10^{0}$ $-$3.31$\, \times\, 10^{0}$ $-$3.32$\, \times\, 10^{0}$ $-$3.29$\, \times\, 10^{0}$ $-$3.28$\, \times\, 10^{0}$
    $f_{21}$ $-$1.00$\, \times\, 10^{1}$ $-$9.64$\, \times\, 10^{0}$ $-$8.37$\, \times\, 10^{0}$ $-$6.61$\, \times\, 10^{0}$ $-$4.69$\, \times\, 10^{0}$
    $f_{22}$ $-$9.99$\, \times\, 10^{0}$ $-$9.84$\, \times\, 10^{0}$ $-$9.70$\, \times\, 10^{0}$ $-$7.07$\, \times\, 10^{0}$ $-$6.21$\, \times\, 10^{0}$
    $f_{23}$ $-$1.03$\, \times\, 10^{1}$ $-$1.03$\, \times\, 10^{1}$ $-$8.62$\, \times\, 10^{0}$ $-$6.92$\, \times\, 10^{0}$ $-$4.93$\, \times\, 10^{0}$
    Friedman排序 $\textbf{1.89}$ 1.91 2.41 3.78 5
    下载: 导出CSV

    表  2  用Friedman检验法(显著性水平0.05)比较参数$p_s$

    Table  2  Comparison of $p_s$ with Friedman test (significance value 0.05)

    Function $p_s=0.2$ $p_s=0.4$ $p_s=0.6$ $p_s=0.8$ $p_s=1.0$ $p_s=1.2$ $p_s=1.4$ $p_s=1.6$ $p_s=1.8$
    $f_1$ 3.73$\, \times\, 10^{2}$ 1.04$\, \times\, 10^{-28}$ 2.76$\, \times\, 10^{-40}$ 4.57$\, \times\, 10^{-33}$ 3.22$\, \times\, 10^{-23}$ 1.11$\, \times\, 10^{-13}$ 5.40$\, \times\, 10^{-6}$ 7.63$\, \times\, 10^{-1}$ 5.05$\, \times\, 10^{2 }$
    $f_2$ 8.94$\, \times\, 10^{-1}$ 3.43$\, \times\, 10^{-27}$ 5.25$\, \times\, 10^{-27}$ 3.75$\, \times\, 10^{-22}$ 3.18$\, \times\, 10^{-16}$ 2.06$\, \times\, 10^{-10}$ 1.67$\, \times\, 10^{-5}$ 6.46$\, \times\, 10^{-1}$ 2.81$\, \times\, 10^{1 }$
    $f_3$ 6.14$\, \times\, 10^{3}$ 3.43$\, \times\, 10^{3}$ 1.52$\, \times\, 10^{3}$ 2.48$\, \times\, 10^{2}$ 1.47$\, \times\, 10^{2}$ 3.02$\, \times\, 10^{3}$ 1.41$\, \times\, 10^{4}$ 3.29$\, \times\, 10^{4}$ 5.52$\, \times\, 10^{4}$
    $f_4$ 4.28$\, \times\, 10^{1}$ 2.60$\, \times\, 10^{1}$ 1.33$\, \times\, 10^{1}$ 1.52$\, \times\, 10^{0}$ 4.22$\, \times\, 10^{-1}$ 2.12$\, \times\, 10^{0}$ 1.03$\, \times\, 10^{1}$ 3.12$\, \times\, 10^{1}$ 4.95$\, \times\, 10^{1 }$
    $f_5$ 1.46$\, \times\, 10^{5}$ 1.80$\, \times\, 10^{2}$ 8.00$\, \times\, 10^{1}$ 4.79$\, \times\, 10^{1}$ 5.29$\, \times\, 10^{1}$ 7.48$\, \times\, 10^{1}$ 1.92$\, \times\, 10^{3}$ 8.76$\, \times\, 10^{3}$ 4.36$\, \times\, 10^{5 }$
    $f_6$ 3.85$\, \times\, 10^{2}$ 4.76$\, \times\, 10^{0}$ 1.96$\, \times\, 10^{-1}$ 3.92$\, \times\, 10^{-2}$ 0.00$\, \times\, 10^{0}$ 0.00$\, \times\, 10^{0}$ 0.00$\, \times\, 10^{0}$ 3.27$\, \times\, 10^{0}$ 6.33$\, \times\, 10^{2}$
    $f_7$ 3.49$\, \times\, 10^{-1}$ 7.34$\, \times\, 10^{-2}$ 3.53$\, \times\, 10^{-2}$ 2.24$\, \times\, 10^{-2}$ 1.27$\, \times\, 10^{-2}$ 9.89$\, \times\, 10^{-3}$ 3.69$\, \times\, 10^{-2}$ 1.38$\, \times\, 10^{-1}$ 1.71$\, \times\, 10^{0 }$
    $f_8$ $-$1.17$\, \times\, 10^{4}$ $-$1.18$\, \times\, 10^{4}$ $-$1.17$\, \times\, 10^{4}$ $-$1.15$\, \times\, 10^{4}$ $-$1.15$\, \times\, 10^{4}$ $-$1.10$\, \times\, 10^{4}$ $-$1.04$\, \times\, 10^{4}$ $-$9.75$\, \times\, 10^{3}$ $-$8.78$\, \times\, 10^{3}$
    $f_9$ 2.03$\, \times\, 10^{1}$ 1.04$\, \times\, 10^{1}$ 1.04$\, \times\, 10^{1}$ 1.08$\, \times\, 10^{1}$ 1.23$\, \times\, 10^{1}$ 1.37$\, \times\, 10^{1}$ 1.83$\, \times\, 10^{1}$ 4.22$\, \times\, 10^{1}$ 1.48$\, \times\, 10^{2 }$
    $f_{10}$ 4.97$\, \times\, 10^{0}$ 1.22$\, \times\, 10^{0}$ 5.48$\, \times\, 10^{-2}$ 1.39$\, \times\, 10^{-14}$ 1.53$\, \times\, 10^{-12}$ 1.31$\, \times\, 10^{-7}$ 3.92$\, \times\, 10^{-1}$ 6.94$\, \times\, 10^{0}$ 1.83$\, \times\, 10^{1}$
    $f_{11}$ 3.83$\, \times\, 10^{0}$ 1.72$\, \times\, 10^{-2}$ 1.78$\, \times\, 10^{-3}$ 5.73$\, \times\, 10^{-4}$ 6.10$\, \times\, 10^{-4}$ 6.34$\, \times\, 10^{-6}$ 3.03$\, \times\, 10^{-3}$ 8.30$\, \times\, 10^{-1}$ 5.52$\, \times\, 10^{0}$
    $f_{12}$ 1.21$\, \times\, 10^{3}$ 3.14$\, \times\, 10^{-1}$ 5.90$\, \times\, 10^{-2}$ 8.13$\, \times\, 10^{-3}$ 4.07$\, \times\, 10^{-3}$ 1.63$\, \times\, 10^{-2}$ 4.30$\, \times\, 10^{-3}$ 4.53$\, \times\, 10^{0}$ 8.29$\, \times\, 10^{4 }$
    $f_{13}$ 1.15$\, \times\, 10^{5}$ 1.55$\, \times\, 10^{1}$ 2.98$\, \times\, 10^{0}$ 7.40$\, \times\, 10^{-2}$ 5.95$\, \times\, 10^{-2}$ 4.78$\, \times\, 10^{-3}$ 3.13$\, \times\, 10^{0}$ 5.90$\, \times\, 10^{1}$ 5.70$\, \times\, 10^{5 }$
    $f_{14}$ 1.91$\, \times\, 10^{0}$ 1.19$\, \times\, 10^{0}$ 1.04$\, \times\, 10^{0}$ 1.10$\, \times\, 10^{0}$ 1.02$\, \times\, 10^{0}$ 1.02$\, \times\, 10^{0}$ 1.08$\, \times\, 10^{0}$ 1.04$\, \times\, 10^{0}$ 1.04$\, \times\, 10^{0}$
    $f_{15}$ 9.93$\, \times\, 10^{-4}$ 6.09$\, \times\, 10^{-4}$ 5.93$\, \times\, 10^{-4}$ 5.50$\, \times\, 10^{-4}$ 5.65$\, \times\, 10^{-4}$ 5.46$\, \times\, 10^{-4}$ 6.20$\, \times\, 10^{-4}$ 6.55$\, \times\, 10^{-4}$ 7.44$\, \times\, 10^{-4 }$
    $f_{16}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.02$\, \times\, 10^{0}$ $-$1.02$\, \times\, 10^{0}$ $-$1.01$\, \times\, 10^{0}$
    $f_{17}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1 }$
    $f_{18}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0 }$
    $f_{19}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0 }$
    $f_{20}$ $-$3.27$\, \times\, 10^{0}$ $-$3.28$\, \times\, 10^{0}$ $-$3.27$\, \times\, 10^{0}$ $-$3.29$\, \times\, 10^{0}$ $-$3.30$\, \times\, 10^{0}$ $-$3.29$\, \times\, 10^{0}$ $-$3.27$\, \times\, 10^{0}$ $-$3.24$\, \times\, 10^{0}$ $-$3.23$\, \times\, 10^{0}$
    $f_{21}$ $-$8.15$\, \times\, 10^{0}$ $-$9.38$\, \times\, 10^{0}$ $-$9.66$\, \times\, 10^{0}$ $-$9.99$\, \times\, 10^{0}$ $-$1.00$\, \times\, 10^{1}$ $-$9.90$\, \times\, 10^{0}$ $-$9.93$\, \times\, 10^{0}$ $-$9.94$\, \times\, 10^{0}$ $-$9.24$\, \times\, 10^{0}$
    $f_{22}$ $-$7.29$\, \times\, 10^{0}$ $-$9.42$\, \times\, 10^{0}$ $-$9.75$\, \times\, 10^{0}$ $-$1.02$\, \times\, 10^{1}$ $-$9.99$\, \times\, 10^{0}$ $-$1.04$\, \times\, 10^{1}$ $-$1.01$\, \times\, 10^{1}$ $-$9.99$\, \times\, 10^{0}$ $-$9.93$\, \times\, 10^{0}$
    $f_{23}$ $-$8.11$\, \times\, 10^{0}$ $-$9.00$\, \times\, 10^{0}$ $-$1.02$\, \times\, 10^{1}$ $-$9.89$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{1}$ $-$1.03$\, \times\, 10^{1}$ $-$1.02$\, \times\, 10^{1}$ $-$1.04$\, \times\, 10^{1}$ $-$9.56$\, \times\, 10^{0 }$
    Friedman排序 7.04 4.78 3.65 3.04 $\textbf{2.65}$ 3.39 5.30 6.61 8.52
    下载: 导出CSV

    表  3  用Friedman检验法(显著性水平0.05)比较参数$p_m$

    Table  3  Comparison of $p_m$ with Friedman test (significance value 0.05)

    Function $p_m=0.0$ $p_m=0.1$ $p_m=0.2$ $p_m=0.3$ $p_m=0.4$ $p_m=0.5$ $p_m=0.6$ $p_m=0.7$ $p_m=0.8$ $p_m=0.9$ $p_m=1.0$
    $f_1$ 9.97$\, \times\, 10^{3}$ 3.43$\, \times\, 10^{3}$ 5.14$\, \times\, 10^{2}$ 5.55$\, \times\, 10^{0}$ 7.19$\, \times\, 10^{-26}$ 2.80$\, \times\, 10^{-54}$ 8.01$\, \times\, 10^{-49 }$ 1.87$\, \times\, 10^{-40}$ 6.54$\, \times\, 10^{-32}$ 3.22$\, \times\, 10^{-23}$ 4.53$\, \times\, 10^{4}$
    $f_2$ 6.45$\, \times\, 10^{1}$ 4.08$\, \times\, 10^{1}$ 1.82$\, \times\, 10^{1}$ 4.30$\, \times\, 10^{0}$ 9.80$\, \times\, 10^{-1}$ 3.92$\, \times\, 10^{-1 }$ 1.96$\, \times\, 10^{-1}$ 3.41$\, \times\, 10^{-27}$ 7.72$\, \times\, 10^{-22}$ 3.18$\, \times\, 10^{-16}$ 1.03$\, \times\, 10^{2 }$
    $f_3$ 2.91$\, \times\, 10^{4}$ 2.22$\, \times\, 10^{4}$ 1.58$\, \times\, 10^{4}$ 7.56$\, \times\, 10^{3}$ 2.82$\, \times\, 10^{3}$ 2.42$\, \times\, 10^{3 }$ 2.12$\, \times\, 10^{3}$ 1.53$\, \times\, 10^{3}$ 1.08$\, \times\, 10^{3}$ 1.47$\, \times\, 10^{2}$ 5.68$\, \times\, 10^{4 }$
    $f_4$ 5.37$\, \times\, 10^{1}$ 4.72$\, \times\, 10^{1}$ 4.00$\, \times\, 10^{1}$ 2.87$\, \times\, 10^{1}$ 7.44$\, \times\, 10^{0}$ 8.10$\, \times\, 10^{-1 }$ 2.19$\, \times\, 10^{-1}$ 1.69$\, \times\, 10^{-1}$ 2.25$\, \times\, 10^{-1}$ 4.22$\, \times\, 10^{-1}$ 7.67$\, \times\, 10^{1 }$
    $f_5$ 8.71$\, \times\, 10^{6}$ 2.01$\, \times\, 10^{6}$ 2.25$\, \times\, 10^{5}$ 6.37$\, \times\, 10^{3}$ 2.00$\, \times\, 10^{3}$ 1.87$\, \times\, 10^{3 }$ 9.59$\, \times\, 10^{1}$ 3.69$\, \times\, 10^{1}$ 5.80$\, \times\, 10^{1}$ 5.29$\, \times\, 10^{1}$ 1.20$\, \times\, 10^{8 }$
    $f_6$ 1.20$\, \times\, 10^{4}$ 5.37$\, \times\, 10^{3}$ 1.58$\, \times\, 10^{3}$ 3.35$\, \times\, 10^{2}$ 7.03$\, \times\, 10^{1}$ 1.51$\, \times\, 10^{1 }$ 1.76$\, \times\, 10^{0}$ 1.37$\, \times\, 10^{0}$ 1.57$\, \times\, 10^{-1}$ 0.00$\, \times\, 10^{0}$ 4.40$\, \times\, 10^{4}$
    $f_7$ 7.62$\, \times\, 10^{0}$ 2.64$\, \times\, 10^{0}$ 1.28$\, \times\, 10^{0}$ 5.08$\, \times\, 10^{-1}$ 2.24$\, \times\, 10^{-1}$ 1.45$\, \times\, 10^{-1 }$ 6.80$\, \times\, 10^{-2}$ 4.88$\, \times\, 10^{-2}$ 2.65$\, \times\, 10^{-2}$ 1.27$\, \times\, 10^{-2}$ 5.67$\, \times\, 10^{1 }$
    $f_8$ $-$7.10$\, \times\, 10^{3}$ $-$7.71$\, \times\, 10^{3}$ $-$8.25$\, \times\, 10^{3}$ $-$8.69$\, \times\, 10^{3}$ $-$8.81$\, \times\, 10^{3}$ $-$9.31$\, \times\, 10^{3 }$ $-$9.73$\, \times\, 10^{3}$ $-$1.00$\, \times\, 10^{4}$ $-$1.05$\, \times\, 10^{4}$ $-$1.15$\, \times\, 10^{4}$ $-$4.61$\, \times\, 10^{3 }$
    $f_9$ 1.89$\, \times\, 10^{2}$ 1.58$\, \times\, 10^{2}$ 1.39$\, \times\, 10^{2}$ 1.08$\, \times\, 10^{2}$ 9.11$\, \times\, 10^{1}$ 7.68$\, \times\, 10^{1 }$ 5.27$\, \times\, 10^{1}$ 3.90$\, \times\, 10^{1}$ 2.66$\, \times\, 10^{1}$ 1.23$\, \times\, 10^{1}$ 3.14$\, \times\, 10^{2 }$
    $f_{10}$ 1.70$\, \times\, 10^{1}$ 1.44$\, \times\, 10^{1}$ 1.10$\, \times\, 10^{1}$ 6.69$\, \times\, 10^{0}$ 4.13$\, \times\, 10^{0}$ 2.45$\, \times\, 10^{0 }$ 8.55$\, \times\, 10^{-1}$ 2.13$\, \times\, 10^{-1}$ 2.26$\, \times\, 10^{-2}$ 1.53$\, \times\, 10^{-12}$ 1.97$\, \times\, 10^{1}$
    $f_{11}$ 9.11$\, \times\, 10^{1}$ 3.01$\, \times\, 10^{1}$ 6.56$\, \times\, 10^{0}$ 9.69$\, \times\, 10^{-1}$ 5.39$\, \times\, 10^{-2}$ 1.93$\, \times\, 10^{-2 }$ 9.21$\, \times\, 10^{-3}$ 3.09$\, \times\, 10^{-3}$ 9.18$\, \times\, 10^{-4}$ 6.10$\, \times\, 10^{-4}$ 3.83$\, \times\, 10^{2 }$
    $f_{12}$ 5.70$\, \times\, 10^{6}$ 8.31$\, \times\, 10^{5}$ 2.34$\, \times\, 10^{3}$ 4.86$\, \times\, 10^{0}$ 7.95$\, \times\, 10^{-1}$ 5.19$\, \times\, 10^{-1 }$ 2.66$\, \times\, 10^{-1}$ 2.20$\, \times\, 10^{-1}$ 7.14$\, \times\, 10^{-2}$ 4.07$\, \times\, 10^{-3}$ 2.24$\, \times\, 10^{8}$
    $f_{13}$ 2.39$\, \times\, 10^{7}$ 3.24$\, \times\, 10^{6}$ 8.92$\, \times\, 10^{4}$ 6.24$\, \times\, 10^{1}$ 6.66$\, \times\, 10^{0}$ 2.05$\, \times\, 10^{0 }$ 2.45$\, \times\, 10^{0}$ 9.56$\, \times\, 10^{-1}$ 5.66$\, \times\, 10^{-1}$ 5.95$\, \times\, 10^{-2}$ 5.39$\, \times\, 10^{8}$
    $f_{14}$ 1.94$\, \times\, 10^{0}$ 2.02$\, \times\, 10^{0}$ 1.41$\, \times\, 10^{0}$ 1.11$\, \times\, 10^{0}$ 1.09$\, \times\, 10^{0}$ 9.98$\, \times\, 10^{-1}$ 1.04$\, \times\, 10^{0}$ 9.98$\, \times\, 10^{-1}$ 1.02$\, \times\, 10^{0}$ 1.02$\, \times\, 10^{0}$ 2.26$\, \times\, 10^{0 }$
    $f_{15}$ 6.63$\, \times\, 10^{-3}$ 3.32$\, \times\, 10^{-3}$ 3.82$\, \times\, 10^{-3}$ 2.99$\, \times\, 10^{-3}$ 3.22$\, \times\, 10^{-3}$ 2.02$\, \times\, 10^{-3}$ 9.00$\, \times\, 10^{-4}$ 1.13$\, \times\, 10^{-3}$ 4.26$\, \times\, 10^{-4}$ 5.65$\, \times\, 10^{-4}$ 4.09$\, \times\, 10^{-3 }$
    $f_{16}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0 }$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.02$\, \times\, 10^{0 }$
    $f_{17}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$
    $f_{18}$ 3.53$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.53$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.01$\, \times\, 10^{0}$
    $f_{19}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0 }$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0 }$
    $f_{20}$ $-$3.26$\, \times\, 10^{0}$ $-$3.27$\, \times\, 10^{0}$ $-$3.28$\, \times\, 10^{0}$ $-$3.27$\, \times\, 10^{0}$ $-$3.27$\, \times\, 10^{0}$ $-$3.26$\, \times\, 10^{0}$ $-$3.25$\, \times\, 10^{0}$ $-$3.26$\, \times\, 10^{0}$ $-$3.26$\, \times\, 10^{0}$ $-$3.30$\, \times\, 10^{0}$ $-$3.08$\, \times\, 10^{0 }$
    $f_{21}$ $-$5.73$\, \times\, 10^{0}$ $-$5.38$\, \times\, 10^{0}$ $-$5.43$\, \times\, 10^{0}$ $-$6.01$\, \times\, 10^{0}$ $-$5.10$\, \times\, 10^{0}$ $-$5.66$\, \times\, 10^{0 }$ $-$6.61$\, \times\, 10^{0}$ $-$8.13$\, \times\, 10^{0}$ $-$9.10$\, \times\, 10^{0}$ $-$1.00$\, \times\, 10^{1}$ $-$5.09$\, \times\, 10^{0 }$
    $f_{22}$ $-$6.02$\, \times\, 10^{0}$ $-$5.84$\, \times\, 10^{0}$ $-$6.17$\, \times\, 10^{0}$ $-$5.37$\, \times\, 10^{0}$ $-$6.82$\, \times\, 10^{0}$ $-$6.55$\, \times\, 10^{0 }$ $-$7.66$\, \times\, 10^{0}$ $-$8.83$\, \times\, 10^{0}$ $-$1.02$\, \times\, 10^{1}$ $-$9.99$\, \times\, 10^{0}$ $-$4.70$\, \times\, 10^{0 }$
    $f_{23}$ $-$5.27$\, \times\, 10^{0}$ $-$5.23$\, \times\, 10^{0}$ $-$5.98$\, \times\, 10^{0}$ $-$5.17$\, \times\, 10^{0}$ $-$6.45$\, \times\, 10^{0}$ $-$7.78$\, \times\, 10^{0}$ $-$7.84$\, \times\, 10^{0}$ $-$9.05$\, \times\, 10^{0}$ $-$9.78$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{1}$ $-$5.04$\, \times\, 10^{0 }$
    Friedman排序 6.60 6.05 5.70 6.25 5.15 5.00 5.45 5.00 5.20 $\textbf{4.90}$ 10.70
    下载: 导出CSV

    表  4  用Friedman检验法(显著性水平0.05)比较权重系数$w_{gp}$, $w_{rp}$, $w_{ga}$, $w_{ra}$

    Table  4  Comparison of $w_{gp}$, $w_{rp}$, $w_{ga}$, $w_{ra}$ with Friedman test (significance value 0.05)

    Function $w_{gp}=w_{rp}=w_{ga}=w_{ra}=1$ $w_{gp}$, $w_{rp}$, $w_{ga}$, $w_{ra}$为随机数
    $f_1$ 3.22$\, \times\, 10^{-23}$ 1.79$\, \times\, 10^{-19}$
    $f_2$ 3.18$\, \times\, 10^{-16}$ 5.71$\, \times\, 10^{-14}$
    $f_3$ 1.47$\, \times\, 10^{2}$ 7.04$\, \times\, 10^{2 }$
    $f_4$ 4.22$\, \times\, 10^{-1}$ 8.05$\, \times\, 10^{-1}$
    $f_5$ 5.29$\, \times\, 10^{1}$ 5.91$\, \times\, 10^{1}$
    $f_6$ 0.00$\, \times\, 10^{0}$ 1.96$\, \times\, 10^{-2}$
    $f_7$ 1.27$\, \times\, 10^{-2}$ 1.52$\, \times\, 10^{-2 }$
    $f_8$ $-$1.15$\, \times\, 10^{4}$ $-$1.10$\, \times\, 10^{4 }$
    $f_9$ 1.23$\, \times\, 10^{1}$ 1.87$\, \times\, 10^{1}$
    $f_{10}$ 1.53$\, \times\, 10^{-12}$ 1.10$\, \times\, 10^{-10 }$
    $f_{11}$ 6.10$\, \times\, 10^{-4}$ 2.17$\, \times\, 10^{-4} $
    $f_{12}$ 4.07$\, \times\, 10^{-3}$ 1.63$\, \times\, 10^{-2 }$
    $f_{13}$ 5.95$\, \times\, 10^{-2}$ 1.88$\, \times\, 10^{-1 }$
    $f_{14}$ 1.02$\, \times\, 10^{0}$ 1.08$\, \times\, 10^{0 }$
    $f_{15}$ 5.65$\, \times\, 10^{-4}$ 5.45$\, \times\, 10^{-4}$
    $f_{16}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0 }$
    $f_{17}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$
    $f_{18}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0 }$
    $f_{19}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0 }$
    $f_{20}$ $-$3.30$\, \times\, 10^{0}$ $-$3.27$\, \times\, 10^{0 }$
    $f_{21}$ $-$1.00$\, \times\, 10^{1}$ $-$9.96$\, \times\, 10^{0 }$
    $f_{22}$ $-$9.99$\, \times\, 10^{0}$ $-$1.00$\, \times\, 10^{1}$
    $f_{23}$ $-$1.03$\, \times\, 10^{1}$ $-$9.52$\, \times\, 10^{0 }$
    Friedman排序 $\textbf{1.13}$ 1.87
    下载: 导出CSV

    表  5  FECO优化23个测试函数的优化结果

    Table  5  Optimization results of FECO for 23 benchmark functions

    Function 最好Best 最差Worst 平均Mean 标准差StdDev
    $f_1$ 1.27$\, \times\, 10^{-24}$ 1.15$\, \times\, 10^{-22}$ 3.22$\, \times\, 10^{-23}$ 2.71$\, \times\, 10^{-23 }$
    $f_2$ 1.16$\, \times\, 10^{-16}$ 9.84$\, \times\, 10^{-16}$ 3.18$\, \times\, 10^{-16}$ 1.68$\, \times\, 10^{-16 }$
    $f_3$ 1.43$\, \times\, 10^{1}$ 4.65$\, \times\, 10^{2}$ 1.47$\, \times\, 10^{2}$ 1.16$\, \times\, 10^{2 }$
    $f_4$ 1.51$\, \times\, 10^{-1}$ 1.59$\, \times\, 10^{0}$ 4.22$\, \times\, 10^{-1}$ 2.59$\, \times\, 10^{-1 }$
    $f_5$ 1.18$\, \times\, 10^{0}$ 1.91$\, \times\, 10^{2}$ 5.29$\, \times\, 10^{1}$ 3.84$\, \times\, 10^{1 }$
    $f_6$ 0.00$\, \times\, 10^{0}$ 0.00$\, \times\, 10^{0}$ 0.00$\, \times\, 10^{0}$ 0.00$\, \times\, 10^{0 }$
    $f_7$ 4.17$\, \times\, 10^{-3}$ 2.87$\, \times\, 10^{-2}$ 1.27$\, \times\, 10^{-2}$ 5.10$\, \times\, 10^{-3 }$
    $f_8$ $-$1.22$\, \times\, 10^{4}$ $-$1.09$\, \times\, 10^{4}$ $-$1.15$\, \times\, 10^{4}$ 3.29$\, \times\, 10^{2 }$
    $f_9$ 4.97$\, \times\, 10^{0}$ 2.49$\, \times\, 10^{1}$ 1.23$\, \times\, 10^{1}$ 5.24$\, \times\, 10^{0 }$
    $f_{10}$ 4.88$\, \times\, 10^{-13}$ 4.58$\, \times\, 10^{-12}$ 1.53$\, \times\, 10^{-12}$ 8.44$\, \times\, 10^{-13 }$
    $f_{11}$ 0.00$\, \times\, 10^{0}$ 1.64$\, \times\, 10^{-2}$ 6.10$\, \times\, 10^{-4}$ 2.85$\, \times\, 10^{-3 }$
    $f_{12}$ 7.25$\, \times\, 10^{-24}$ 1.04$\, \times\, 10^{-1}$ 4.07$\, \times\, 10^{-3}$ 2.03$\, \times\, 10^{-2 }$
    $f_{13}$ 8.50$\, \times\, 10^{-20}$ 3.02$\, \times\, 10^{0}$ 5.95$\, \times\, 10^{-2}$ 4.23$\, \times\, 10^{-1 }$
    $f_{14}$ 9.98$\, \times\, 10^{-1}$ 1.99$\, \times\, 10^{0}$ 1.02$\, \times\, 10^{0}$ 1.40$\, \times\, 10^{-1 }$
    $f_{15}$ 3.08$\, \times\, 10^{-4}$ 8.08$\, \times\, 10^{-4}$ 5.65$\, \times\, 10^{-4}$ 1.50$\, \times\, 10^{-4 }$
    $f_{16}$ $-$1.03$\, \times\, 10^{0}$ $-$1.00$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ 6.52$\, \times\, 10^{-3 }$
    $f_{17}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 1.06$\, \times\, 10^{-6 }$
    $f_{18}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.58$\, \times\, 10^{-14 }$
    $f_{19}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ 6.57$\, \times\, 10^{-7 }$
    $f_{20}$ $-$3.32$\, \times\, 10^{0}$ $-$3.20$\, \times\, 10^{0}$ $-$3.30$\, \times\, 10^{0}$ 3.84$\, \times\, 10^{-2 }$
    $f_{21}$ $-$1.02$\, \times\, 10^{1}$ $-$5.10$\, \times\, 10^{0}$ $-$1.00$\, \times\, 10^{1}$ 7.22$\, \times\, 10^{-1 }$
    $f_{22}$ $-$1.04$\, \times\, 10^{1}$ $-$4.64$\, \times\, 10^{0}$ $-$9.99$\, \times\, 10^{0}$ 1.36$\, \times\, 10^{0 }$
    $f_{23}$ $-$1.05$\, \times\, 10^{1}$ $-$5.18$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{1}$ 9.72$\, \times\, 10^{-1 }$
    下载: 导出CSV

    表  6  FECO算法与其他启发式算法的比较(1)

    Table  6  Comparison between FECO and other heuristic algorithms (1)

    GA CEP FEP CES FES DE G3PCX PSO
    $f_1$ 3.17$\, \times\, 10^{0}$ 2.20$\, \times\, 10^{-4}$ 5.70$\, \times\, 10^{-4}$ 3.40$\, \times\, 10^{-5}$ 2.50$\, \times\, 10^{-4}$ 6.58$\, \times\, 10^{-6}$ 6.40$\, \times\, 10^{-79}$ 3.69$\, \times\, 10^{-37 }$
    算法排序 15 11 13 10 12 9 1 2
    $f_2$ 5.77$\, \times\, 10^{-1}$ 2.60$\, \times\, 10^{-3}$ 8.10$\, \times\, 10^{-3}$ 2.10$\, \times\, 10^{-2}$ 6.00$\, \times\, 10^{-2}$ 2.89$\, \times\, 10^{-4}$ 2.80$\, \times\, 10^{1}$ 2.92$\, \times\, 10^{-24}$
    算法排序 14 8 9 10 12 6 16 1
    $f_3$ 9.75$\, \times\, 10^{3}$ 5.00$\, \times\, 10^{-2}$ 1.60$\, \times\, 10^{-2}$ 1.30$\, \times\, 10^{-4}$ 1.40$\, \times\, 10^{-3}$ 1.21$\, \times\, 10^{4}$ 1.06$\, \times\, 10^{-76}$ 1.20$\, \times\, 10^{-3}$
    算法排序 15 10 9 6 8 16 1 7
    $f_4$ 7.96$\, \times\, 10^{0}$ 2.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{-1}$ 3.50$\, \times\, 10^{-1}$ 5.50$\, \times\, 10^{-3}$ 5.79$\, \times\, 10^{0}$ 4.54$\, \times\, 10^{1}$ 4.12$\, \times\, 10^{-1 }$
    算法排序 14 11 7 8 2 12 15 9
    $f_5$ 3.39$\, \times\, 10^{2}$ 6.17$\, \times\, 10^{0}$ 5.06$\, \times\, 10^{0}$ 6.69$\, \times\, 10^{0}$ 3.33$\, \times\, 10^{1}$ 9.34$\, \times\, 10^{1}$ 3.09$\, \times\, 10^{0}$ 3.74$\, \times\, 10^{1 }$
    算法排序 15 3 2 4 8 14 1 9
    $f_6$ 3.70$\, \times\, 10^{0}$ 5.78$\, \times\, 10^{2}$ 0.00$\, \times\, 10^{0}$ 4.11$\, \times\, 10^{2}$ 0.00$\, \times\, 10^{0}$ 0.00$\, \times\, 10^{0}$ 9.46$\, \times\, 10^{1}$ 1.46$\, \times\, 10^{-1 }$
    算法排序 13 16 1 15 1 1 14 9
    $f_7$ 1.05$\, \times\, 10^{-1}$ 1.80$\, \times\, 10^{-2}$ 7.60$\, \times\, 10^{-3}$ 3.00$\, \times\, 10^{-2}$ 1.20$\, \times\, 10^{-2}$ 3.97$\, \times\, 10^{-2}$ 9.80$\, \times\, 10^{-1}$ 9.90$\, \times\, 10^{-3 }$
    算法排序 14 9 4 10 6 11 16 5
    $f_8$ $-$1.26$\, \times\, 10^{4}$ $-$7.92$\, \times\, 10^{3}$ $-$1.26$\, \times\, 10^{4}$ $-$7.55$\, \times\, 10^{3}$ $-$1.26$\, \times\, 10^{4}$ $-$1.26$\, \times\, 10^{4}$ $-$2.58$\, \times\, 10^{3}$ $-$9.66$\, \times\, 10^{3 }$
    算法排序 5 10 7 11 6 2 15 9
    $f_9$ 6.51$\, \times\, 10^{-1}$ 8.90$\, \times\, 10^{1}$ 4.60$\, \times\, 10^{-2}$ 7.08$\, \times\, 10^{1}$ 1.60$\, \times\, 10^{-1}$ 7.26$\, \times\, 10^{-5}$ 1.74$\, \times\, 10^{2}$ 2.08$\, \times\, 10^{1 }$
    算法排序 8 14 5 13 6 2 15 11
    $f_{10}$ 8.68$\, \times\, 10^{-1}$ 9.20$\, \times\, 10^{0}$ 1.80$\, \times\, 10^{-2}$ 9.07$\, \times\, 10^{0}$ 1.20$\, \times\, 10^{-2}$ 7.14$\, \times\, 10^{-4}$ 1.35$\, \times\, 10^{1}$ 1.34$\, \times\, 10^{-3}$
    算法排序 11 14 8 13 7 4 15 5
    $f_{11}$ 1.00$\, \times\, 10^{0}$ 8.60$\, \times\, 10^{-2}$ 1.60$\, \times\, 10^{-2}$ 3.80$\, \times\, 10^{-1}$ 3.70$\, \times\, 10^{-2}$ 9.05$\, \times\, 10^{-5}$ 1.13$\, \times\, 10^{-2}$ 2.32$\, \times\, 10^{-1 }$
    算法排序 14 11 7 13 9 1 6 12
    $f_{12}$ 4.36$\, \times\, 10^{-2}$ 1.76$\, \times\, 10^{0}$ 9.20$\, \times\, 10^{-6}$ 1.18$\, \times\, 10^{0}$ 2.80$\, \times\, 10^{-2}$ 1.89$\, \times\, 10^{-7}$ 4.59$\, \times\, 10^{0}$ 3.95$\, \times\, 10^{-2 }$
    算法排序 9 13 3 12 7 2 15 8
    $f_{13}$ 1.68$\, \times\, 10^{-1}$ 1.40$\, \times\, 10^{0}$ 1.60$\, \times\, 10^{-4}$ 1.39$\, \times\, 10^{0}$ 4.70$\, \times\, 10^{-5}$ 9.52$\, \times\, 10^{-7}$ 2.35$\, \times\, 10^{1}$ 5.05$\, \times\, 10^{-2 }$
    算法排序 9 12 5 11 4 2 15 7
    $f_{14}$ 9.99$\, \times\, 10^{-1}$ 1.66$\, \times\, 10^{0}$ 1.22$\, \times\, 10^{0}$ 2.16$\, \times\, 10^{0}$ 1.20$\, \times\, 10^{0}$ 1.58$\, \times\, 10^{0}$ 1.23$\, \times\, 10^{1}$ 1.02$\, \times\, 10^{0 }$
    算法排序 5 11 9 13 8 10 16 7
    $f_{15}$ 7.09$\, \times\, 10^{-3}$ 4.70$\, \times\, 10^{-4}$ 5.00$\, \times\, 10^{-4}$ 1.20$\, \times\, 10^{-3}$ 9.70$\, \times\, 10^{-4}$ 5.37$\, \times\, 10^{-4}$ 5.33$\, \times\, 10^{-4}$ 3.81$\, \times\, 10^{-4 }$
    算法排序 16 4 5 14 13 7 6 3
    $f_{16}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.02$\, \times\, 10^{0}$ $-$4.93$\, \times\, 10^{-1}$ $-$1.02$\, \times\, 10^{0 }$
    算法排序 11 9 9 4 4 12 14 13
    $f_{17}$ 4.04$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 4.00$\, \times\, 10^{-1}$ 5.56$\, \times\, 10^{1}$ 4.04$\, \times\, 10^{-1 }$
    算法排序 13 7 7 7 7 12 16 13
    $f_{18}$ 7.50$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.02$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.48$\, \times\, 10^{0}$ 8.67$\, \times\, 10^{0}$ 3.01$\, \times\, 10^{0 }$
    算法排序 15 2 13 2 2 14 16 11
    $f_{19}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.60$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0 }$
    算法排序 7 9 9 9 9 8 15 13
    $f_{20}$ $-$3.26$\, \times\, 10^{0}$ $-$3.28$\, \times\, 10^{0}$ $-$3.27$\, \times\, 10^{0}$ $-$3.24$\, \times\, 10^{0}$ $-$3.23$\, \times\, 10^{0}$ $-$3.32$\, \times\, 10^{0}$ $-$1.98$\, \times\, 10^{-1}$ $-$3.18$\, \times\, 10^{0 }$
    算法排序 10 7 8 11 12 4 15 13
    $f_{21}$ $-$5.17$\, \times\, 10^{0}$ $-$6.86$\, \times\, 10^{0}$ $-$5.52$\, \times\, 10^{0}$ $-$6.96$\, \times\, 10^{0}$ $-$5.54$\, \times\, 10^{0}$ $-$8.74$\, \times\, 10^{0}$ $-$7.48$\, \times\, 10^{-1}$ $-$7.54$\, \times\, 10^{0 }$
    算法排序 14 8 12 7 11 4 15 5
    $f_{22}$ $-$5.44$\, \times\, 10^{0}$ $-$8.27$\, \times\, 10^{0}$ $-$5.52$\, \times\, 10^{0}$ $-$8.31$\, \times\, 10^{0}$ $-$6.76$\, \times\, 10^{0}$ $-$9.20$\, \times\, 10^{0}$ $-$9.47$\, \times\, 10^{-1}$ $-$8.36$\, \times\, 10^{0 }$
    算法排序 14 8 13 7 11 5 15 6
    $f_{23}$ $-$4.91$\, \times\, 10^{0}$ $-$9.10$\, \times\, 10^{0}$ $-$6.57$\, \times\, 10^{0}$ $-$8.50$\, \times\, 10^{0}$ $-$7.63$\, \times\, 10^{0}$ $-$9.23$\, \times\, 10^{0}$ $-$1.13$\, \times\, 10^{0}$ $-$8.94$\, \times\, 10^{0 }$
    算法排序 14 7 13 9 10 6 15 8
    Friedman排序 11.957 9.304 7.739 9.522 7.609 7.13 12.522 8.087
    总排序 14 12 8 13 7 5 15 9
    下载: 导出CSV

    表  7  FECO算法与其他启发式算法的比较(2)

    Table  7  Comparison between FECO and other heuristic algorithms (2)

    GSO GSA NFESA RCBBO RCCRO GWO WOA FECO
    $f_1$ 1.95$\, \times\, 10^{-8}$ 2.53$\, \times\, 10^{-16}$ 8.10$\, \times\, 10^{2}$ 1.39$\, \times\, 10^{-3}$ 6.43$\, \times\, 10^{-7}$ 6.59$\, \times\, 10^{-28}$ 1.41$\, \times\, 10^{-30}$ 3.22$\, \times\, 10^{-23}$
    算法排序 7 6 16 14 8 4 3 5
    $f_2$ 3.70$\, \times\, 10^{-5}$ 5.57$\, \times\, 10^{-2}$ 4.07$\, \times\, 10^{0}$ 7.99$\, \times\, 10^{-2}$ 2.20$\, \times\, 10^{-3}$ 7.18$\, \times\, 10^{-17}$ 1.06$\, \times\, 10^{-21}$ 3.18$\, \times\, 10^{-16}$
    算法排序 5 11 15 13 7 3 2 4
    $f_3$ 5.78$\, \times\, 10^{0}$ 8.97$\, \times\, 10^{2}$ 1.79$\, \times\, 10^{-6}$ 2.27$\, \times\, 10^{1}$ 2.97$\, \times\, 10^{-7}$ 3.29$\, \times\, 10^{-6}$ 5.36$\, \times\, 10^{-7}$ 1.47$\, \times\, 10^{2 }$
    算法排序 11 14 4 12 2 5 3 13
    $f_4$ 1.08$\, \times\, 10^{-1}$ 7.35$\, \times\, 10^{0}$ 5.11$\, \times\, 10^{1}$ 3.09$\, \times\, 10^{-2}$ 9.32$\, \times\, 10^{-3}$ 5.61$\, \times\, 10^{-7}$ 7.26$\, \times\, 10^{-2}$ 4.22$\, \times\, 10^{-1}$
    算法排序 6 13 16 4 3 1 5 10
    $f_5$ 4.98$\, \times\, 10^{1}$ 6.75$\, \times\, 10^{1}$ 1.81$\, \times\, 10^{6}$ 5.54$\, \times\, 10^{1}$ 2.71$\, \times\, 10^{1}$ 2.68$\, \times\, 10^{1}$ 2.79$\, \times\, 10^{1}$ 5.29$\, \times\, 10^{1}$
    算法排序 10 13 16 12 6 5 7 11
    $f_6$ 1.60$\, \times\, 10^{-2}$ 2.50$\, \times\, 10^{-16}$ 4.51$\, \times\, 10^{-1}$ 0.00$\, \times\, 10^{0}$ 0.00$\, \times\, 10^{0}$ 8.17$\, \times\, 10^{-1}$ 3.12$\, \times\, 10^{0}$ 0.00$\, \times\, 10^{0}$
    算法排序 8 7 10 1 1 11 12 1
    $f_7$ 7.38$\, \times\, 10^{-2}$ 8.94$\, \times\, 10^{-2}$ 3.86$\, \times\, 10^{-1}$ 1.75$\, \times\, 10^{-2}$ 5.41$\, \times\, 10^{-3}$ 2.21$\, \times\, 10^{-3}$ 1.43$\, \times\, 10^{-3}$ 1.27$\, \times\, 10^{-2}$
    算法排序 12 13 15 8 3 2 1 7
    $f_8$ $-$1.26$\, \times\, 10^{4}$ $-$2.82$\, \times\, 10^{3}$ 7.35$\, \times\, 10^{3}$ $-$1.26$\, \times\, 10^{4}$ $-$1.26$\, \times\, 10^{4}$ $-$6.12$\, \times\, 10^{3}$ $-$5.08$\, \times\, 10^{3}$ $-$1.15$\, \times\, 10^{4}$
    算法排序 1 14 16 2 2 12 13 8
    $f_9$ 1.02$\, \times\, 10^{0}$ 2.60$\, \times\, 10^{1}$ 2.12$\, \times\, 10^{2}$ 2.62$\, \times\, 10^{-2}$ 9.08$\, \times\, 10^{-4}$ 3.11$\, \times\, 10^{-1}$ 0.00$\, \times\, 10^{0}$ 1.23$\, \times\, 10^{1}$
    算法排序 9 12 16 4 3 7 1 10
    $f_{10}$ 2.65$\, \times\, 10^{-5}$ 6.21$\, \times\, 10^{-2}$ 1.67$\, \times\, 10^{1}$ 2.51$\, \times\, 10^{-2}$ 1.94$\, \times\, 10^{-3}$ 1.06$\, \times\, 10^{-13}$ 7.40$\, \times\, 10^{0}$ 1.53$\, \times\, 10^{-12}$
    算法排序 3 10 16 9 6 1 12 2
    $f_{11}$ 3.08$\, \times\, 10^{-2}$ 2.77$\, \times\, 10^{1}$ 5.67$\, \times\, 10^{0}$ 8.49$\, \times\, 10^{-2}$ 1.12$\, \times\, 10^{-2}$ 4.49$\, \times\, 10^{-3}$ 2.89$\, \times\, 10^{-4}$ 6.10$\, \times\, 10^{-4}$
    算法排序 8 16 15 10 5 4 2 3
    $f_{12}$ 2.76$\, \times\, 10^{-11}$ 1.80$\, \times\, 10^{0}$ 4.43$\, \times\, 10^{5}$ 3.28$\, \times\, 10^{-5}$ 2.07$\, \times\, 10^{-2}$ 5.34$\, \times\, 10^{-2}$ 3.40$\, \times\, 10^{-1}$ 4.07$\, \times\, 10^{-3}$
    算法排序 1 14 16 4 6 10 11 5
    $f_{13}$ 4.69$\, \times\, 10^{-5}$ 8.89$\, \times\, 10^{0}$ 3.95$\, \times\, 10^{6}$ 3.72$\, \times\, 10^{-4}$ 7.05$\, \times\, 10^{-7}$ 6.54$\, \times\, 10^{-1}$ 1.89$\, \times\, 10^{0}$ 5.95$\, \times\, 10^{-2 }$
    算法排序 3 14 16 6 1 10 13 8
    $f_{14}$ 9.98$\, \times\, 10^{-1}$ 5.86$\, \times\, 10^{0}$ 9.98$\, \times\, 10^{-1}$ 9.98$\, \times\, 10^{-1}$ 9.98$\, \times\, 10^{-1}$ 4.04$\, \times\, 10^{0}$ 2.11$\, \times\, 10^{0}$ 1.02$\, \times\, 10^{0 }$
    算法排序 1 15 4 3 1 14 12 6
    $f_{15}$ 3.77$\, \times\, 10^{-4}$ 3.67$\, \times\, 10^{-3}$ 7.89$\, \times\, 10^{-4}$ 7.86$\, \times\, 10^{-4}$ 5.56$\, \times\, 10^{-4}$ 3.37$\, \times\, 10^{-4}$ 5.72$\, \times\, 10^{-4}$ 5.65$\, \times\, 10^{-4}$
    算法排序 2 15 12 11 8 1 10 9
    $f_{16}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ 1.06$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ 1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{0}$
    算法排序 3 1 16 7 4 15 1 8
    $f_{17}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 4.24$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$ 3.98$\, \times\, 10^{-1}$
    算法排序 4 1 15 11 4 3 6 2
    $f_{18}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.01$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$ 3.00$\, \times\, 10^{0}$
    算法排序 2 2 9 12 10 8 2 1
    $f_{19}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ 1.47$\, \times\, 10^{-1}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0}$ $-$3.86$\, \times\, 10^{0 }$
    算法排序 2 4 16 6 1 5 14 3
    $f_{20}$ $-$3.27$\, \times\, 10^{0}$ $-$3.32$\, \times\, 10^{0}$ 9.34$\, \times\, 10^{-1}$ $-$3.32$\, \times\, 10^{0}$ $-$3.32$\, \times\, 10^{0}$ $-$3.29$\, \times\, 10^{0}$ $-$2.98$\, \times\, 10^{0}$ $-$3.30$\, \times\, 10^{0}$
    算法排序 9 2 16 3 1 6 14 5
    $f_{21}$ $-$6.09$\, \times\, 10^{0}$ $-$5.96$\, \times\, 10^{0}$ 6.80$\, \times\, 10^{0}$ $-$5.51$\, \times\, 10^{0}$ $-$1.01$\, \times\, 10^{1}$ $-$1.02$\, \times\, 10^{1}$ $-$7.05$\, \times\, 10^{0}$ $-$1.00$\, \times\, 10^{1}$
    算法排序 9 10 16 13 2 1 6 3
    $f_{22}$ $-$6.55$\, \times\, 10^{0}$ $-$9.68$\, \times\, 10^{0}$ 6.85$\, \times\, 10^{0}$ $-$6.80$\, \times\, 10^{0}$ $-$1.04$\, \times\, 10^{1}$ $-$1.04$\, \times\, 10^{1}$ $-$8.18$\, \times\, 10^{0}$ $-$9.99$\, \times\, 10^{0}$
    算法排序 12 4 16 10 2 1 9 3
    $f_{23}$ $-$7.40$\, \times\, 10^{0}$ $-$1.05$\, \times\, 10^{1}$ 6.81$\, \times\, 10^{0}$ $-$7.28$\, \times\, 10^{0}$ $-$1.05$\, \times\, 10^{1}$ $-$1.05$\, \times\, 10^{1}$ $-$9.34$\, \times\, 10^{0}$ $-$1.03$\, \times\, 10^{1}$
    算法排序 11 1 16 12 3 2 5 4
    Friedman排序 6.043 9.217 14.043 8.13 3.87 5.696 7.13 5.696
    总排序 4 11 16 10 1 2 5 2
    下载: 导出CSV

    表  8  FECO算法与其他启发式算法对于CEC2015测试函数的比较

    Table  8  Comparison between FECO and other heuristic algorithms for CEC2015 functions

    Function CCLSHADE ICMLSP PSO NFESA FECO
    $f_{CEC15\_1}$ 2.28$\, \times\, 10^{-14}~(-)$ 1.03$\, \times\, 10^{-13}~(-)$ 4.70$\, \times\, 10^{6}~(+)$ 3.87$\, \times\, 10^{8}~(+)$ 3.31$\, \times\, 10^{6}$
    $f_{CEC15\_2}$ 5.07$\, \times\, 10^{-14}~(-)$ 4.05$\, \times\, 10^{-5}~(-)$ 5.94$\, \times\, 10^{3 }~(\sim)$ 2.62$\, \times\, 10^{10}~(+)$ 5.97$\, \times\, 10^{3}$
    $f_{CEC15\_3}$ 2.02$\, \times\, 10^{1}~(+)$ 2.00$\, \times\, 10^{1}~(-)$ 2.09$\, \times\, 10^{1}~(+)$ 2.09$\, \times\, 10^{1}~(+)$ 2.01$\, \times\, 10^{1}$
    $f_{CEC15\_4}$ 4.92$\, \times\, 10^{0}~(-)$ 2.31$\, \times\, 10^{2}~(+)$ 5.63$\, \times\, 10^{1}~(+)$ 3.15$\, \times\, 10^{2}~(+)$ 4.70$\, \times\, 10^{1 }$
    $f_{CEC15\_5}$ 3.00$\, \times\, 10^{2}~(-)$ 4.03$\, \times\, 10^{3}~(+)$ 2.74$\, \times\, 10^{3}~(+)$ 7.08$\, \times\, 10^{3}~(+)$ 1.81$\, \times\, 10^{3 }$
    $f_{CEC15\_6}$ 8.17$\, \times\, 10^{1}~(-)$ 1.47$\, \times\, 10^{3}~(-)$ 3.64$\, \times\, 10^{5}~(+)$ 7.72$\, \times\, 10^{6}~(+)$ 3.19$\, \times\, 10^{5 }$
    $f_{CEC15\_7}$ 1.50$\, \times\, 10^{0}~(-)$ 2.07$\, \times\, 10^{1}~(+)$ 9.90$\, \times\, 10^{0} ~ (\sim)$ 1.24$\, \times\, 10^{2}~(+)$ 9.40$\, \times\, 10^{0 }$
    $f_{CEC15\_8}$ 1.58$\, \times\, 10^{1}~(-)$ 9.42$\, \times\, 10^{2}~(-)$ 1.52$\, \times\, 10^{5}~(+)$ 1.77$\, \times\, 10^{6}~(+)$ 9.43$\, \times\, 10^{4 }$
    $f_{CEC15\_9}$ 1.03$\, \times\, 10^{2}~(\sim)$ 1.63$\, \times\, 10^{2}~(+)$ 1.03$\, \times\, 10^{2 } ~ (\sim)$ 2.22$\, \times\, 10^{2}~(+)$ 1.03$\, \times\, 10^{2}$
    $f_{CEC15\_10}$ 6.06$\, \times\, 10^{2}~(-)$ 1.43$\, \times\, 10^{3}~(-)$ 1.11$\, \times\, 10^{5}~(-)$ 9.96$\, \times\, 10^{6}~(+)$ 2.93$\, \times\, 10^{5 }$
    $f_{CEC15\_11}$ 4.01$\, \times\, 10^{2}~(-)$ 1.12$\, \times\, 10^{3}~(+)$ 6.26$\, \times\, 10^{2}~(+)$ 8.82$\, \times\, 10^{2}~(+)$ 5.29$\, \times\, 10^{2 }$
    $f_{CEC15\_12}$ 1.04$\, \times\, 10^{2}~(-)$ 1.61$\, \times\, 10^{2}~(+)$ 1.17$\, \times\, 10^{2}~(+)$ 1.55$\, \times\, 10^{2}~(+)$ 1.06$\, \times\, 10^{2 }$
    $f_{CEC15\_13}$ 2.60$\, \times\, 10^{-2}~(-)$ 8.53$\times 10^{-2}~(+)$ 8.90$\, \times\, 10^{-2}~(+)$ 6.49$\times 10^{0}~(+)$ 2.65$\, \times\, 10^{-2 }$
    $f_{CEC15\_14}$ 3.28$\, \times\, 10^{4}~(-)$ 4.21$\, \times\, 10^{4}~(+)$ 3.51$\, \times\, 10^{4}~(+)$ 5.52$\, \times\, 10^{4}~(+)$ 3.36$\, \times\, 10^{4 }$
    $f_{CEC15\_15}$ 1.00$\, \times\, 10^{2}~(-)$ 1.27$\, \times\, 10^{2}~(+)$ 1.00$\, \times\, 10^{2}~(-)$ 6.28$\, \times\, 10^{3}~(+)$ 1.00$\, \times\, 10^{2}$
    下载: 导出CSV
  • [1] Kirkpatrick S, Gelatt C D Jr, Vecchi M P. Optimization by simulated annealing. Science, 1983, 220(4598): 671-680 doi: 10.1126/science.220.4598.671
    [2] Goldberg D E. Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: Addison-Wesley, 1989.
    [3] Dorigo M, Stützle T. Ant Colony Optimization. Cambridge, MA: MIT Press, 2004.
    [4] Kennedy J, Eberhart R C. Swarm Intelligence. San Francisco, CA: Morgan Kaufmann, 2001.
    [5] Karaboga D, Basturk B. A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm. Journal of Global Optimization, 2007, 39(3): 459-471 doi: 10.1007/s10898-007-9149-x
    [6] Yang X S. Firefly algorithm, stochastic test functions and design optimisation. International Journal of Bio-Inspired Computation, 2010, 2(2): 78-84 doi: 10.1504/IJBIC.2010.032124
    [7] Mirjalili S, Mirjalili S M, Lewis A. Grey wolf optimizer. Advances in Engineering Software, 2014, 69: 46-61 doi: 10.1016/j.advengsoft.2013.12.007
    [8] Wang G G, Deb S, Cui Z H. Monarch Butterfly Optimization, Neural Computing and Applications. New York, NY, USA: Springer, 2015. 1-20
    [9] Mirjalili S, Lewis A. The whale optimization algorithm. Advances in Engineering Software, 2016, 95: 51-67 doi: 10.1016/j.advengsoft.2016.01.008
    [10] 肖辉辉, 万常选, 段艳明, 谭黔林.基于引力搜索机制的花朵授粉算法.自动化学报, 2017, 43(4): 576-594 doi: 10.16383/j.aas.2017.c160146

    Xiao Hui-Hui, Wan Chang-Xuan, Duan Yan-Ming, Tan Qian-Lin. Flower pollination algorithm based on gravity search mechanism. Acta Automatica Sinica, 2017, 43(4): 576-594 doi: 10.16383/j.aas.2017.c160146
    [11] Dhiman G, Kumar V. Spotted hyena optimizer: a novel bio-inspired based metaheuristic technique for engineering applications. Advances in Engineering Software, 2017, 114: 48-70 doi: 10.1016/j.advengsoft.2017.05.014
    [12] Slowik A, Kwasnicka H. Nature inspired methods and their industry applications—swarm intelligence algorithms. IEEE Transactions on Industrial Informatics, 2018, 14(3): 1004-1015 doi: 10.1109/TII.2017.2786782
    [13] 冯友兰.中国哲学简史.北京:新世界出版社, 2004.

    Feng You-Lan. A Brief History of Chinese Philosophy. Beijing: New World Press, 2004.
    [14] Tam S C, Tam H K, Tam L M, Zhang T. A new optimization method, the algorithm of changes, for Bin Packing Problem. In: Proceedings of the IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications. Changsha, China: IEEE, 2010. 994-999
    [15] Zhao R. Survivable topology design of hybrid fiber-VDSL access networks with a novel metaheuristic. In: Proceedings of the 5th Advanced International Conference on Telecommunications. Venice/Mestre, Italy, 2009.
    [16] Cui Y H, Guo R K, Guo D. A naïve five-element string algorithm. Journal of Software, 2009, 4(9): 925-934 http://d.old.wanfangdata.com.cn/OAPaper/oai_doaj-articles_321e5ca99cad37eaa2938d505e255ee4
    [17] Punnathanam V, Kotecha P. Yin-Yang-pair Optimization: a novel lightweight optimization algorithm. Engineering Applications of Artificial Intelligence, 2016, 54: 62-79 doi: 10.1016/j.engappai.2016.04.004
    [18] Liu M D. Five-elements cycle optimization algorithm for the travelling salesman problem. In: Proceedings of the 18th International Conference on Advanced Robotics (ICAR). Hong Kong, China, 2017.
    [19] Liu M D. Five-elements cycle optimization algorithm for solving continuous optimization problems. In: Proceedings of the IEEE 4th International Conference on Soft Computing & Machine Intelligence (ISCMI). Mauritius: IEEE, 2017. 75-79
    [20] Yao X, Liu Y, Lin G M. Evolutionary programming made faster. IEEE Transactions on Evolutionary Computation, 1999, 3(2): 82-102 doi: 10.1109/4235.771163
    [21] Derrac J, García S, Molina D, Herrera F. A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm and Evolutionary Computation, 2011, 1(1): 3-18
    [22] Yao X, Liu Y. Fast evolution strategies. In: Proceedings of the 6th International Conference on Evolutionary Programming VI. Berlin: Springer, 1997. 151-162
    [23] Storn R, Price K. Differential evolution——a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization, 1997, 11(4): 341-359 doi: 10.1023/A:1008202821328
    [24] Deb K, Anand A, Joshi D. A computationally efficient evolutionary algorithm for real-parameter optimization. Evolutionary Computation, 2002, 10(4): 371-395 doi: 10.1162/106365602760972767
    [25] He S, Wu Q H, Saunders J R. Group search optimizer: an optimization algorithm inspired by animal searching behavior. IEEE Transactions on Evolutionary Computation, 2009, 13(5): 973-990 doi: 10.1109/TEVC.2009.2011992
    [26] Rashedi E, Nezamabadi-Pour H, Saryazdi S. GSA: a gravitational search algorithm. Information Sciences, 2009, 179(13): 2232-2248 doi: 10.1016/j.ins.2009.03.004
    [27] Gong W Y, Cai Z H, Ling C X, Li H. A real-coded biogeography-based optimization with mutation. Applied Mathematics and Computation, 2010, 216(9): 2749-2758 doi: 10.1016/j.amc.2010.03.123
    [28] Lam A Y S, Li V O K, Yu J J Q. Real-coded chemical reaction optimization. IEEE Transactions on Evolutionary Computation, 2012, 16(3): 339-353 doi: 10.1109/TEVC.2011.2161091
    [29] Liang J J, Qu B Y, Suganthan P N, Chen Q. Problem Definitions and Evaluation Criteria for the CEC 2015 Competition on Learning-based Real-Parameter Single Objective Optimization, Technical Report, Computational Intelligence Laboratory, Zhengzhou University, Zhengzhou, China and Technical Report, Nanyang Technological University, Singapore, 2014.
    [30] El-Abd M. Cooperative co-evolution using LSHADE with restarts for the CEC15 benchmarks. In: Proceedings of the 2016 IEEE Congress on Evolutionary Computation (CEC). Vancouver, Canada: IEEE, 2016. 4810-4814
    [31] Chen L, Peng C D, Liu H L, Xie S L. An improved covariance matrix leaning and searching preference algorithm for solving CEC 2015 benchmark problems. In: Proceedings of the 2015 IEEE Congress on Evolutionary Computation (CEC). Sendai, Japan: IEEE, 2015. 1041-1045
  • 加载中
图(6) / 表(8)
计量
  • 文章访问数:  3651
  • HTML全文浏览量:  935
  • PDF下载量:  380
  • 被引次数: 0
出版历程
  • 收稿日期:  2017-11-20
  • 录用日期:  2018-07-05
  • 刊出日期:  2020-06-01

目录

    /

    返回文章
    返回