Skip to main content
SpringerLink
Log in
Book cover

Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011 pp 141–149Cite as

A Improved Artificial Fish Swarming Optimization for Economic Load Dispatch with Dynamic Constraints

  • Conference paper
  • First Online:

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 130))

Abstract

Nature Inspired algorithms have been so far proved as some of the best problem solvers. The Artificial Fish Schooling Algorithm (AFSA) which falls under this category has been deployed to solve the classic Economic Load Dispatch problem. A modified implementation has been illustrated in this paper to enhance the precision and speed of the algorithm.

This is a preview of subscription content, 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   169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Li, X.L., Shao, Z.J., Qian, J.X.: An optimizing method based on autonomous animals: fish-swarm algorithm. Systems Engineering Theory & Practice 22(11), 32–38 (2002)

    Google Scholar 

  2. Yazdani, D., Golyari, S., Meybodi, M.R.: A new hybrid algorithm for optimization based on artificial fish swarm algorithm and cellular learning automata. In: 2010 5th International Symposium on Telecommunications (IST), December 4-6, pp. 932–937 (2010), doi:10.1109/ISTEL.2010.5734156

    Google Scholar 

  3. Gao, Y.F., Chen, Y.D.: The optimization of water utilization based on artificial fish-swarm algorithm. In: 2010 Sixth International Conference on Natural Computation (ICNC), August 10-12, vol. 8, pp. 4415–4419 (2010), doi:10.1109/ICNC.2010.5583509

    Google Scholar 

  4. Ma, H., Wang, Y.: An Artificial Fish Swarm Algorithm Based on Chaos Search. In: Fifth International Conference on Natural Computation, ICNC 2009, August 14-16, vol. 4, pp. 118–121 (2009), doi:10.1109/ICNC.2009.148

    Google Scholar 

  5. Xu, H., Li, R., Guo, J., Wang, H.: An Adaptive Meta-cognitive Artificial Fish School Algorithm. In: International Forum on Information Technology and Applications, IFITA 2009, May 15-17, vol. 1, pp. 594–597 (2009), doi:10.1109/IFITA.2009.352

    Google Scholar 

  6. Wang, J.-P., Hu, M.-J.: A Solution for TSP Based on Artificial Fish Algorithm. In: International Conference on Computational Intelligence and Natural Computing, CINC 2009, June 6-7, vol. 2, pp. 26–29 (2009), doi:10.1109/CINC.2009.72

    Google Scholar 

  7. Jiang, M., Zhu, K.: Multiobjective optimization by Artificial Fish Swarm Algorithm. In: IEEE International Conference on Computer Science and Automation Engineering (CSAE 2011), June 10-12, vol. 3, pp. 506–511 (2011), doi:10.1109/CSAE.2011.5952729

    Google Scholar 

  8. Prudhvi, P., Bhaskar, M.M., Maheswarapu, S.: A Big Bang Big Crunch Algorithm (BBBC) for Economic Dispatch with Network Losses and Dynamic Constraints. In: National Conference on Machines and Power System, vol. 1, pp. 203–208 (February 2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, National Institute of Technology, Warangal, India

    Potuganti Prudhvi, Adapa Sudarshan & Chakradhar Bezawada

Authors
  1. Potuganti Prudhvi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Adapa Sudarshan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chakradhar Bezawada
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Potuganti Prudhvi .

Editor information

Editors and Affiliations

  1. , Department of Mathematics, Indian Institute of Technology Roorkee, Uttarakhand, Roorkee, 247667, India

    Kusum Deep

  2. Department of Mathematics and, Computer Science, Liverpool Hope University, Hope Park, Liverpool, L16 9JD, United Kingdom

    Atulya Nagar

  3. , Department of Paper Technology, Indian Institute of Technology Roorkee, Uttarakhand, Roorkee, 247667, India

    Millie Pant

  4. Information Technology and Management, ABV-Indian Institute of, 109, E- Block, Gwalior, 474010, India

    Jagdish Chand Bansal

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer India Pvt. Ltd.

About this paper

Cite this paper

Prudhvi, P., Sudarshan, A., Bezawada, C. (2012). A Improved Artificial Fish Swarming Optimization for Economic Load Dispatch with Dynamic Constraints. In: Deep, K., Nagar, A., Pant, M., Bansal, J. (eds) Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011. Advances in Intelligent and Soft Computing, vol 130. Springer, India. https://doi.org/10.1007/978-81-322-0487-9_14

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-0487-9_14

  • Published:

  • Publisher Name: Springer, India

  • Print ISBN: 978-81-322-0486-2

  • Online ISBN: 978-81-322-0487-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation