Skip to main content
SpringerLink
Log in
Book cover

Advances in Multimedia, Software Engineering and Computing Vol.2 pp 139–144Cite as

An Improved Shuffled Frog Leaping Algorithm for TSP

  • Conference paper

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 129))

Abstract

With the optimization theory of Shuffled Frog Leaping Algorithm (SFLA), the paper extended the traditional model of SFLA for solution by using the encoding basing on urban-based sequence and using the new method for individual. This paper also improved the SFLA for the traveling salesman problem. The simulation results show the effectiveness of the proposed method and strategy.

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   259.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   329.99
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. Kang, Z., Qiang, X.-L., Tong, X.-J.: Algorithm for TSP. Computer Engineering and Applications 43(29), 43–37 (2007)

    Google Scholar 

  2. Ye, L., Ni, Z.-W., Liu, H.-T.: An improved genetic algorithm for TSP. Computer Engineering and Applications 43(6), 65–68 (2007)

    Google Scholar 

  3. Zhong, Y., Yuan, C.-W.: Ant colony optimization algorithm for Chinese traveling salesman problem. Circuits and Systems Journal 9(3), 122–126 (2004)

    MathSciNet  Google Scholar 

  4. Yang, L.-Y.: Simulated Annealing Algorithm for TSP. Microelectronics and Computer 24(5), 193–196 (2007)

    Article  Google Scholar 

  5. Eusuff, M., Lansey, K.: Optimization of water distribution network design using the shuffled frog leaping algorithm. Water Resour Plan Manage 129(3), 210–225 (2003)

    Article  Google Scholar 

  6. Thyer, M., Kuczera, G.: Probabilistic optimization for conceptual rainfall run off models: A comparison of the shuffled complex evolution and simulated annealing algorithms. Water Resources 35(3), 767–773

    Google Scholar 

  7. Xun, Z.-H., Gu, X.-S.: Immune scheduling algorithm for Flow Shop problems under uncertainty. Systems Engineering Journal 20(4), 374–375 (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Information Science and Engineering, Henan University of Technology, ZhengZhou, China

    Zhoufang Li & Yuhua Wang

Authors
  1. Zhoufang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yuhua Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Wuhan Section, International Science & Education Researcher Association, Special No.1, Jiangxia Road of Wuhan, Wuhan, China, People’s Republic

    David Jin

  2. ISER Association, Guangshan Road, Baoli Garden 1, 430072, Wuhan, China, People’s Republic

    Sally Lin

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Li, Z., Wang, Y. (2011). An Improved Shuffled Frog Leaping Algorithm for TSP. In: Jin, D., Lin, S. (eds) Advances in Multimedia, Software Engineering and Computing Vol.2. Advances in Intelligent and Soft Computing, vol 129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25986-9_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-25986-9_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25985-2

  • Online ISBN: 978-3-642-25986-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation