Investigating the Impact of Alternative Evolutionary Selection Strategies on Multi-method Global Optimization

被引:0
|
作者
Grobler, Jacomine [1 ]
Engelbrecht, Andries P. [2 ]
Kendall, Graham [3 ]
Yadavalli, V. S. S. [1 ,2 ]
机构
[1] Univ Pretoria, Dept Ind & Syst Engn, ZA-0002 Pretoria, South Africa
[2] Univ Pretoria, Dept Comp Sci, Pretoria, South Africa
[3] Univ Nottingham, Sch Comp Sci, Nottingham NG7 2RD, England
来源
2011 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2011年
关键词
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Algorithm selection is an important consideration in multi-method global optimization. This paper investigates the use of various algorithm selection strategies derived from well known evolutionary selection mechanisms. Selection strategy performance is evaluated on a diverse set of floating point benchmark problems and meaningful conclusions are drawn with regard to the impact of selective pressure on algorithm selection in a multi-method environment.
引用
收藏
页码:2337 / 2344
页数:8
相关论文
共 50 条
  • [31] What is the Social Impact of ADHD in Girls? A Multi-Method Assessment
    Jeneva L. Ohan
    Charlotte Johnston
    Journal of Abnormal Child Psychology, 2007, 35 : 239 - 250
  • [32] Global Social Tolerance Index and multi-method country rankings sensitivity
    Stelios H Zanakis
    William Newburry
    Vasyl Taras
    Journal of International Business Studies, 2016, 47 : 480 - 497
  • [33] Comparison of alternative route selection strategies based on simulation optimization
    Ye Bojia
    Sherry, Lance
    Chen Chun-Hung
    Tian Yong
    CHINESE JOURNAL OF AERONAUTICS, 2016, 29 (06) : 1749 - 1761
  • [34] Comparison of alternative route selection strategies based on simulation optimization
    Ye Bojia
    Lance Sherry
    Chen Chun-Hung
    Tian Yong
    Chinese Journal of Aeronautics , 2016, (06) : 1749 - 1761
  • [35] Comparison of alternative route selection strategies based on simulation optimization
    Ye Bojia
    Lance Sherry
    Chen ChunHung
    Tian Yong
    Chinese Journal of Aeronautics, 2016, 29 (06) : 1749 - 1761
  • [36] Impact of Evolutionary Community Detection Algorithms for Edge Selection Strategies
    Barsocchi, Paolo
    Chessa, Stefano
    Foschini, Luca
    Belli, Dimitri
    Girolami, Michele
    2020 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2020,
  • [37] TensorCRO: A TensorFlow-based implementation of a multi-method ensemble for optimization
    Palomo-Alonso, A.
    Costa, V. G.
    Moreno-Saavedra, L. M.
    Lorente-Ramos, E.
    Perez-Aracil, J.
    Pedreira, C. E.
    Salcedo-Sanz, S.
    EXPERT SYSTEMS, 2024, 41 (12)
  • [38] Taboo evolutionary programming: a new method of global optimization
    Ji, Mingjun
    Klinowski, Jacek
    PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2006, 462 (2076): : 3613 - 3627
  • [39] The discrete gradient evolutionary strategy method for global optimization
    Abbass, HA
    Bagirov, AM
    Zhang, J
    CEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS, 2003, : 435 - 442
  • [40] Automated Selection of Evolutionary Multi-objective Optimization Algorithms
    Tian, Ye
    Peng, Shichen
    Rodemann, Tobias
    Zhang, Xingyi
    Jin, Yaochu
    2019 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI 2019), 2019, : 3225 - 3232