Genetic algorithms using low-discrepancy sequences

被引:0
|
作者
Kimura, Shuhei [1 ]
Matsumura, Koki [1 ]
机构
[1] Tottori Univ, Dept Informat & Knowlege Engn, Fac Engn, Tottori 680, Japan
关键词
genetic algorithm; random number generator; pseudo-random number sequence; low-discrepancy sequence;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The-random number generator is one of the important components of evolutionary algorithms (EAs). Therefore, when we try to solve function optimization problems using EAs, we must carefully choose a good pseudo-random number generator. In EAs, the pseudo-random number generator is often used for creating uniformly distributed individuals. As the low-discrepancy sequences allow us to create individuals more uniformly than the random number sequences, we apply the low-discrepancy sequence generator, instead of the pseudo-random number the search performances of EAs.
引用
下载
收藏
页码:1341 / 1346
页数:6
相关论文
共 50 条
  • [41] Influence of Initializing Krill Herd Algorithm With Low-Discrepancy Sequences
    Agushaka, Ovre Jeffrey
    Ezugwu, Absalom El-Shamir
    IEEE ACCESS, 2020, 8 : 210886 - 210909
  • [42] A hybrid meta-heuristic for global optimisation using low-discrepancy sequences of points
    Georgieva, Antoniya
    Jordanov, Ivan
    COMPUTERS & OPERATIONS RESEARCH, 2010, 37 (03) : 456 - 469
  • [43] Computation of Critical Points of Mixtures Using Particle Swarm Optimization with Low-Discrepancy Sequences
    Henderson, Nelio
    De Moura Menezes, Anderson Alvarenga
    Sacco, Wagner F.
    Barufatti, Nelza E.
    CHEMICAL ENGINEERING COMMUNICATIONS, 2015, 202 (11) : 1478 - 1492
  • [44] Using low-discrepancy sequences and the Crofton formula to compute surface areas of geometric models
    Li, XQ
    Wang, WP
    Martin, RR
    Bowyer, A
    COMPUTER-AIDED DESIGN, 2003, 35 (09) : 771 - 782
  • [45] Initializing PSO with Probability Distributions and Low-discrepancy Sequences: The Comparative Results
    Thangaraj, Radha
    Pant, Millie
    Deep, Kusum
    2009 WORLD CONGRESS ON NATURE & BIOLOGICALLY INSPIRED COMPUTING (NABIC 2009), 2009, : 1120 - +
  • [46] Random sampling from low-discrepancy sequences:: Applications to option pricing
    Ökten, G
    MATHEMATICAL AND COMPUTER MODELLING, 2002, 35 (11-12) : 1221 - 1234
  • [47] On the use of low-discrepancy sequences in non-holonomic motion planning
    Sánchez, A
    Zapata, R
    Lanzoni, C
    2003 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-3, PROCEEDINGS, 2003, : 3764 - 3769
  • [48] ALGORITHM-738 - PROGRAMS TO GENERATE NIEDERREITERS LOW-DISCREPANCY SEQUENCES
    BRATLEY, P
    FOX, BL
    NIEDERREITER, H
    ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE, 1994, 20 (04): : 494 - 495
  • [49] Performance evaluation of predictive models for Poisson’s equations by PINN using low-discrepancy sequences
    Daido University, Japan
    Trans. Jpn. Soc. Comput. Eng. Sci.,
  • [50] LOW-DISCREPANCY POINT SETS
    NIEDERREITER, H
    MONATSHEFTE FUR MATHEMATIK, 1986, 102 (02): : 155 - 167