A Differential Evolution Algorithm based on Self-Adapting Mountain-climbing Operator

被引:2
|
作者
Lei, Sheng [1 ]
Liu, Wei [1 ]
Cai, YaoHe [1 ]
机构
[1] Guangdong Univ Technol, Sch Appl Math, Guangzhou 510520, Guangdong, Peoples R China
关键词
Differential Evolution; Mountain-climbing; Self-Adapting;
D O I
10.4028/www.scientific.net/AMM.263-266.2332
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper presents a Differential Evolution algorithm based on Self-Adapting Mountain-climbing operator (LCDE) to overcome the problem of low convergence speed and bad local searching ability in the evolution period. The algorithm dynamically adjusts the value of climb radius during using the information of the individual search efficiency in the search process. The experiment results demonstrate that the new differential evolution algorithm has fast convergence speed and high computation precision.
引用
收藏
页码:2332 / 2338
页数:7
相关论文
共 50 条
  • [1] Self-adapting Scalable Differential Evolution Algorithm
    刘荣辉
    郑建国
    [J]. Journal of Donghua University(English Edition), 2011, 28 (04) : 384 - 390
  • [2] A differential evolution algorithm with self-adapting strategy and control parameters
    Pan, Quan-Ke
    Suganthan, P. N.
    Wang, Ling
    Gao, Liang
    Mallipeddi, R.
    [J]. COMPUTERS & OPERATIONS RESEARCH, 2011, 38 (01) : 394 - 408
  • [3] Self-adapting Differential Evolution Algorithm with Extension Variable Dimension
    Feng Da
    Gao Yuan
    Gao LiQun
    [J]. PROCEEDINGS OF THE 2012 24TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2012, : 751 - 754
  • [4] Self-Adapting Spherical Search Algorithm with Differential Evolution for Global Optimization
    Zhao, Jian
    Zhang, Bochen
    Guo, Xiwang
    Qi, Liang
    Li, Zhiwu
    [J]. MATHEMATICS, 2022, 10 (23)
  • [5] A new differential evolution algorithm with a hybrid mutation operator and self-adapting control parameters for global optimization problems
    Yi, Wenchao
    Gao, Liang
    Li, Xinyu
    Zhou, Yinzhi
    [J]. APPLIED INTELLIGENCE, 2015, 42 (04) : 642 - 660
  • [6] A new differential evolution algorithm with a hybrid mutation operator and self-adapting control parameters for global optimization problems
    Wenchao Yi
    Liang Gao
    Xinyu Li
    Yinzhi Zhou
    [J]. Applied Intelligence, 2015, 42 : 642 - 660
  • [7] Self-adapting Differential Evolution Algorithm with Chaos Random for Global Numerical Optimization
    Yang, Ming
    Guan, Jing
    Cai, Zhihua
    Wang, Lu
    [J]. ADVANCES IN COMPUTATION AND INTELLIGENCE, 2010, 6382 : 112 - +
  • [8] Self-Adapting Approach in Parameter Tuning for Differential Evolution
    Wang, Shir Li
    Theam Foo Ng
    Jamil, Nurul Aini
    Samuri, Suzani Mohamad
    Mailok, Ramlah
    Rahmatullah, Bahbibi
    [J]. 2015 CONFERENCE ON TECHNOLOGIES AND APPLICATIONS OF ARTIFICIAL INTELLIGENCE (TAAI), 2015, : 113 - 119
  • [9] Self-adapting control parameters with multi-parent crossover in differential evolution algorithm
    Fan, Yuanyuan
    Liang, Qingzhong
    Liu, Chao
    Yan, Xuesong
    [J]. INTERNATIONAL JOURNAL OF COMPUTING SCIENCE AND MATHEMATICS, 2015, 6 (01) : 40 - 48
  • [10] COORDINATING EVOLUTION Designing a Self-adapting Distributed Genetic Algorithm
    Chatzinikolaou, Nikolaos
    [J]. ICEIS 2010: PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, VOL 2: ARTIFICIAL INTELLIGENCE AND DECISION SUPPORT SYSTEMS, 2010, : 13 - 20