Skip to main content
SpringerLink
Log in

Asynchronous Island Parallel GA Using Multiform Subpopulations

  • Conference paper
  • First Online:
Simulated Evolution and Learning (SEAL 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1585))

Included in the following conference series:

Abstract

Island Parallel GA divides a population into subpopulations and assigns them to processing elements on a parallel computer. Then each subpopulation searches the optimal solution independently, and exchanges individuals periodically. This exchange operation is called migration. In this research, we propose a new algorithm that migrants are exchanged asynchronously among multiform subpopulations which have different search conditions. The effect of our algorithm on combinational optimization problems was verified by applying the algorithm to Knapsack Problem and Royal Road Functions using parallel computer CRAY-T3E. We obtained the results that our algorithm maintained the population’s diversity effectively and searches building blocks efficiently.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. R. Tanese, Distributed Genetic Algorithm, in Proceedings of the Third International Conference on Genetic Algorithms, pp.434–439, 1989.

    Google Scholar 

  2. M. Munetomo, Y. Takai, and Y. Sato, An Efficient Migration Scheme for Subpopulation-Based Asynchronously Parallel Genetic Algorithms, in Proceedings of the Fifth International Conference on Genetic Algorithms, pp.649, 1993.

    Google Scholar 

  3. M. Ishikawa, T. Toya, and Y. Totoki, Parallel Application Systems in Genetic Processing, in Proceedings of International Symposium on Fifth Generation Computer Systems, pp.129–138, 1994.

    Google Scholar 

  4. S. Tsutsui, and Y. Fujimoto, Forking Genetic Algorithm with Blocking and Shrinking Modes (fGA), in Proceedings of the Fifth International Conference on Genetic Algorithms, pp.206–213, 1993.

    Google Scholar 

  5. M. Mitchell, S. Forrest, and J. H. Holland, The Royal Road for Genetic Algorithms: Fitness Landscapes and GA Performance, in Toward a Practice of Autonomous Systems: Proceedings of the First European Conference on Artificial Life, pp.245–254,1992.

    Google Scholar 

  6. M. Mitchell, J. H. Holland, and S. Forrest, When Will a Genetic Algorithm Out-perform Hill Climbing?, in Advances in Neural Information Processing 6, 1994.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Japan Advanced Institute of Science and Technology, Tatsunokuchi, Ishikawa, 923-1292, Japan

    Hirosuke Horii, Susumu Kunifuji & Teruo Matsuzawa

Authors
  1. Hirosuke Horii
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Susumu Kunifuji
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Teruo Matsuzawa
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Computer Science, University College, UNSW Australian Defence Force Academy, Canberra, ACT, Australia, 2600

    Bob McKay , Xin Yao  & Charles S. Newton ,  & 

  2. Department of Electrical Engineering Korea Advanced Institute of Science and Technology, 373-1, Kusung-dong, Yusung-gu, Taejon-shi, 305-701, Korea

    Jong-Hwan Kim

  3. Department of Information Electronics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8603, Japan

    Takeshi Furuhashi

Rights and permissions

Reprints and permissions

Copyright information

© 1999 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Horii, H., Kunifuji, S., Matsuzawa, T. (1999). Asynchronous Island Parallel GA Using Multiform Subpopulations. In: McKay, B., Yao, X., Newton, C.S., Kim, JH., Furuhashi, T. (eds) Simulated Evolution and Learning. SEAL 1998. Lecture Notes in Computer Science(), vol 1585. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48873-1_17

Download citation

  • DOI: https://doi.org/10.1007/3-540-48873-1_17

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65907-5

  • Online ISBN: 978-3-540-48873-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation