Estimation of the convergence points of a population using an individual pool

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We employ an individual pool to increase the precision of the estimated convergence points of a population by using individual information from past generations. Better individuals from past generations are kept in the pool, and poorer individuals are replaced with new better individuals when the pool becomes full; convergence points for the population are thus estimated using those individuals from the pool that keeps excellent individuals in past generations. The estimated convergence points are used as elite individuals, and replace the worse individuals in current population to accelerate evolutionary computation. Besides the proposed basic pool storage mechanism, we further develop an extended version which enhances the interaction between an individual pool and the population in the latest generation. We evaluate these proposed methods using differential evolution and 14 benchmark functions. The experimental results show that introducing an individual pool can improve the convergence speed and accuracy with the same computational cost, and the extended version could further enhance the accelerated effect in almost all cases.

Original languageEnglish
Title of host publication2017 IEEE 10th International Workshop on Computational Intelligence and Applications, IWCIA 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages67-72
Number of pages6
ISBN (Electronic)9781538604694
DOIs
Publication statusPublished - Dec 13 2017
Event10th IEEE International Workshop on Computational Intelligence and Applications, IWCIA 2017 - Hiroshima, Japan
Duration: Nov 11 2017Nov 12 2017

Publication series

Name2017 IEEE 10th International Workshop on Computational Intelligence and Applications, IWCIA 2017 - Proceedings
Volume2017-December

Other

Other10th IEEE International Workshop on Computational Intelligence and Applications, IWCIA 2017
CountryJapan
CityHiroshima
Period11/11/1711/12/17

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Hardware and Architecture
  • Software
  • Control and Optimization

Fingerprint Dive into the research topics of 'Estimation of the convergence points of a population using an individual pool'. Together they form a unique fingerprint.

  • Cite this

    Yu, J., & Takagi, H. (2017). Estimation of the convergence points of a population using an individual pool. In 2017 IEEE 10th International Workshop on Computational Intelligence and Applications, IWCIA 2017 - Proceedings (pp. 67-72). (2017 IEEE 10th International Workshop on Computational Intelligence and Applications, IWCIA 2017 - Proceedings; Vol. 2017-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWCIA.2017.8203563