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An Artificial Bee Colony Algorithm Approach for Routing in VLSI

  • Hao Zhang
  • Dongyi Ye
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7331)

Abstract

This paper presents an approach that applies the Artificial Bee Colony algorithm to the Two-Terminals-Net-Routing(TTNR) problem in VLSI physical design and compares its performance with the maze algorithm variant known as the state-of-the-art global routing algorithm. An effectively encoding method is described in this paper to solve the TTNR problem. In order to improve the convergence speed of the algorithm, some guiding solutions are employed as the initial solutions. The experimental results demonstrate that Artificial Bee Colony algorithm can find the less cost routing paths for TTNR problems than the maze algorithm.

Keywords

Artificial Bee Colony Algorithm VLSI physical design Global Routing Two-Terminals-Net-Routing 

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References

  1. 1.
    Pan, M., Chu, C.: FastRoute 2.0: A High-quality and Efficient Global Routing. In: 12th Asia and South Pacific Design Automation Conference, pp. 250–255. IEEE Computer Society Press, Washington (2007)CrossRefGoogle Scholar
  2. 2.
    Gao, J.-R., Wu, P.-C., Wang, T.-C.: A new global router for modern designs. In: 13th Asia and South Pacific Design Automation Conference, pp. 232–237. IEEE Computer Society Press, Los Alamitos (2008)Google Scholar
  3. 3.
    Hu, J., Roy, J., Markov, I.: Completing High-Quality Global Routes. In: 19th International Symposium on Physical Design, pp. 35–41. ACM Press, New York (2010)Google Scholar
  4. 4.
    Ayob, M.N., Yusof, Z.M., et al.: A Particle Swarm Optimization Approach for Routing in VLSI. In: 2nd International Conference on Computational Intelligence, Communication Systems and Networks, pp. 49–53. IEEE Press, Liverpool (2010)Google Scholar
  5. 5.
    Arora, T., Moses, M.E.: Ant Colony Optimization for power efficient routing in manhattan and non-manhattan VLSI architectures. In: 2009 Swarm Intelligence Symposium, pp. 137–144. IEEE Press, Nashville (2009)CrossRefGoogle Scholar
  6. 6.
    Wu, P.-C., Gao, J.-R., Wang, T.-C.: A Fast and Stable Algorithm for Obstacle-Avoiding Rectilinear Steiner Minimal Tree Construction. In: 12th Asia and South Pacific Design Automation Conference, pp. 262–267. IEEE Computer Society Press, Washington (2007)CrossRefGoogle Scholar
  7. 7.
    Karaboga, D.: An Idea Based On Honey Bee Swarm For Numerical Optimization, Technical Report-TR06, Erciyes University, Engineering Faculty, Computer Engineering Department (2005)Google Scholar
  8. 8.
    Karaboga, D., Basturk, B.: On the performance of artificial bee colony (abc) algorithm. Applied Soft Computing 8(1), 687–697 (2008)CrossRefGoogle Scholar
  9. 9.
    Chang, Y.-J., Lee, Y.-T., Gao, J.-R., Wu, P.-C., Wang, T.-C.: NTHU-Route 2.0: A Robust Global Router for Modern Designs. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 29(12), 1931–1944 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hao Zhang
    • 1
    • 2
  • Dongyi Ye
    • 1
    • 2
  1. 1.Center for Discrete Mathematics and Theoretical Computer ScienceFuzhou UniversityFuzhouChina
  2. 2.College of Mathematics and Computer ScienceFuzhou UniversityFuzhouChina

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