A new genetic algorithm based on negative selection

被引：0
|
作者：
Li, Na-Na [1 ,2 ]
Gu, Jun-Hua [2 ]
Liu, Bo-Ying [2 ]
机构：
[1] Tianjin Univ, Sch Elect & Informat Engn, Tianjin 300072, Peoples R China
[2] Hebei Univ Technol, Tianjin, Peoples R China
来源：
PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2006年
关键词：
genetic algorithm; immune system; negative selection; function optimization;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Genetic algorithm offers the common frame of resolving optimization problem by imitating biological evolution based on natural selection. However it has some drawbacks such as slow convergence and being premature. In genetic algorithm, individual generated by genetic operation is a bit random and even sometimes more inferior than its parents. So a new operator-negative selection that can filtrate bad-quality individual is introduced to genetic algorithm to speed up its speed of convergence and improve its global searching ability. With this new operator, a new optimization algorithm based genetic algorithm and negative selection is proposed. Furthermore this paper shows its ability to solve the function optimization problem.
引用
收藏
页码：4297 / +
页数：2
相关论文
共 50 条
  • [31] A Clustering Based Genetic Algorithm for Feature Selection
    Rostami, Mehrdad
    Moradi, Parham
    2014 6TH CONFERENCE ON INFORMATION AND KNOWLEDGE TECHNOLOGY (IKT), 2014, : 112 - 116
  • [32] A Clone Selection Based Real-Valued Negative Selection Algorithm
    Zhang, Ruirui
    Xiao, Xin
    COMPLEXITY, 2018,
  • [33] A simulation based genetic algorithm for risk-based partner selection in new product development
    Cao, Hongyi
    Wang, Dingwei
    International Journal of Industrial Engineering : Theory Applications and Practice, 2003, 10 (01): : 16 - 25
  • [34] A simulation based genetic algorithm for risk-based partner selection in new product development
    Cao, HY
    Wang, DW
    INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE, 2003, 10 (01): : 16 - 25
  • [35] Negative Selection Algorithm Based on Double Matching Rules
    Hu, Yu
    Li, Bin
    ADVANCED RESEARCH ON INDUSTRY, INFORMATION SYSTEMS AND MATERIAL ENGINEERING, PTS 1-7, 2011, 204-210 : 42 - +
  • [36] Negative Selection Algorithm Based on Antigen Density Clustering
    Yang, Chao
    Jia, Lin
    Chen, Bing-Qiu
    Wen, Hai-Yang
    IEEE ACCESS, 2020, 8 (08): : 44967 - 44975
  • [37] Improved thresholding based on negative selection algorithm (NSA)
    Mahapatra, Prasant Kumar
    Kaur, Mandeep
    Sethi, Spardha
    Thareja, Rishabh
    Kumar, Amod
    Devi, Swapna
    EVOLUTIONARY INTELLIGENCE, 2014, 6 (03) : 157 - 170
  • [38] Improved Negative Selection Algorithm Based on Bloom Filter
    Zhu Tieying
    Liu Shaojun
    Ma Zhixing
    Zhou Zhiguo
    2009 INTERNATIONAL CONFERENCE ON E-BUSINESS AND INFORMATION SYSTEM SECURITY, VOLS 1 AND 2, 2009, : 1175 - 1178
  • [39] Negative Selection Algorithm Based Intrusion Detection Model
    Tosin, Salau-Ibrahim Taofeekat
    Gbenga, Jimoh Rasheed
    20TH IEEE MEDITERRANEAN ELETROTECHNICAL CONFERENCE (IEEE MELECON 2020), 2020, : 202 - 206
  • [40] A new and fast rival genetic algorithm for feature selection
    Too, Jingwei
    Abdullah, Abdul Rahim
    JOURNAL OF SUPERCOMPUTING, 2021, 77 (03): : 2844 - 2874
12345