Tracer spectrum: a visualisation method for distributed evolutionary computation

被引:0
|
作者
Michael O’Neill
Anthony Brabazon
Erik Hemberg
机构
[1] University College Dublin,Natural Computing Research and Applications Group, Complex and Adaptive Systems Laboratory
关键词
Visualisation; Distributed evolutionary computation;
D O I
暂无
中图分类号
学科分类号
摘要
We present a novel visualisation method for island-based evolutionary algorithms based on the concept of tracers as adopted in medicine and molecular biology to follow a biochemical process. For example, a radioisotope or dye can be used to replace a stable component of a biological compound, and the signal from the radioisotope can be monitored as it passes through the body to measure the compound’s distribution and elimination from the system. In a similar fashion we attach a tracer dye to individuals in each island, where each individual in any one island is marked with the same colour, and each island then has its own unique colour signal. We can then monitor how individuals undergoing migration events are distributed throughout the entire island ecosystem, thereby allowing the user to visually monitor takeover times and the resulting loss of diversity. This is achieved by visualising each island as a spectrum of the tracer dye associated with each individual. Experiments adopting different rates of migration and network connectivity confirm earlier research which predicts that island models are extremely sensitive to the size and frequency of migrations.
引用
收藏
页码:161 / 171
页数:10
相关论文
共 50 条
  • [41] Nonlinear system identification by evolutionary computation and recursive estimation method
    Juang, JG
    Lin, BS
    ACC: Proceedings of the 2005 American Control Conference, Vols 1-7, 2005, : 5073 - 5078
  • [42] A Design Optimization Method with Sparse Scattered Data and Evolutionary Computation
    Liu, Yuxiang
    He, Shipei
    Liu, Wei
    Chen, Xihong
    JOURNAL OF NANOMATERIALS, 2022, 2022
  • [43] Merge of evolutionary computation with gradient based method for optimization problems
    Hewlett, Joel
    Wilarnowski, Bogdan
    Duendar, Guenhan
    2007 IEEE INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS, PROCEEDINGS, VOLS 1-8, 2007, : 3304 - +
  • [44] Rapid Antenna Prototyping Method by Evolutionary Computation and Inkjet Printing
    Shi, Xinyang
    Narusue, Yoshiaki
    Kawahara, Yoshihiro
    Asami, Tohru
    2015 IEEE MTT-S INTERNATIONAL MICROWAVE WORKSHOP SERIES ON ADVANCED MATERIALS AND PROCESSES FOR RF AND THZ APPLICATIONS (IMWS-AMP), 2015, : 258 - 260
  • [45] An Evolutionary Computation Based Feature Selection Method for Intrusion Detection
    Xue, Yu
    Jia, Weiwei
    Zhao, Xuejian
    Pang, Wei
    SECURITY AND COMMUNICATION NETWORKS, 2018,
  • [46] Evolutionary Computation Hybrids with Monte Carlo Method for Differential Equation
    Wu Sheng-Ping
    FOURTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2012), 2012, 8334
  • [47] A Novel Local Community Detection Method Using Evolutionary Computation
    Lyu, Chao
    Shi, Yuhui
    Sun, Lijun
    IEEE TRANSACTIONS ON CYBERNETICS, 2021, 51 (06) : 3348 - 3360
  • [48] An evolutionary computation based method for creative design inspiration generation
    Jia Hao
    Yongjia Zhou
    Qiangfu Zhao
    Qing Xue
    Journal of Intelligent Manufacturing, 2019, 30 : 1673 - 1691
  • [49] From evolutionary computation to natural computation
    Yao, X
    ADAPTIVE COMPUTING IN DESIGN AND MANUFACTURE V, 2002, : 41 - 50
  • [50] An introduction to evolutionary computation and evolutionary algorithms
    Cartwright, HM
    APPLICATIONS OF EVOLUTIONARY COMPUTATION IN CHEMISTRY, 2004, 110 : 1 - 32