Skip to main content
Log in

Channel routing based on ant colony adaptive behavior model

  • Artificial Intelligence
  • Published:
Journal of Computer and Systems Sciences International Aims and scope

Abstract

Based on the comparative analysis of existing approaches and methods for solving routing, routing completion, and rerouting of connections in VLSI, multiagent intelligent optimization methods are used. They are based on the simulation of adaptive behavior of an ant colony. The problem considered in this paper is represented by a set of components of the ant colony algorithm. Heuristics governing the behavior of an ant as it moves in the search graph are developed. A distinctive feature of the proposed algorithm is its capability to take into account some characteristics, such as the distribution of resources, hindrance effects (blockings), the number of transitions between layers, the number of inflections, etc., which are very difficult to take into account when calculating how the wave propagates. The routing algorithm was tested and compared with other known algorithms on a set of benchmarks. Compared with the available algorithms, the quality of solutions is improved by up to 3%. A promising direction of improving the algorithm is the use of an extended routing domain that admits a small increase in the route length but minimizes the hindrances. The efficiency of the algorithm can be improved by an adaptive control of algorithm parameters.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. B. K. Lebedev, Intelligent Procedures for the Synthesis of VLSI Topologies (Taganrog Radiotekhn. Inst., Taganrog, 2003).

    Google Scholar 

  2. C. J. Alpert, P. D. P. Mehta, and S. S. Sapatnekar, Handbook of Algorithms for Physical Design Automation (CRC, New York, 2009).

    MATH  Google Scholar 

  3. O. B. Lebedev, “Global routing based on an ant colony algorithm,” Izv. Yuzhn. Feder. Univ., Ser. Tekhn. Nauki, No. 7 (2011).

    Google Scholar 

  4. B. K. Lebedev and O. B. Lebedev, “Channel routing based on cooperative adaptation,” in Proc. of the Int. Conf. on Artificial Intelligence Systems and CAD, AIS’05 (Fizmatlit, Moscow, 2005), pp. 58–63 [in Russian].

    Google Scholar 

  5. B. K. Lebedev, “Channel routing based on genetic procedures,” Izv. Taganrog Radio Eng. Univ., Dedicated issue on Intelligent CAD Systems, No. 3, 53–60 (1997).

    Google Scholar 

  6. B. K. Lebedev and V. B. Lebedev, “Channel routing procedures based on a combination of swarm intelligence with genetic search, in Problems of the Design of Promising Micro and Nanoelectronic Systems, Ed. by A. L. Stempkovskii (IPPM RAN, Moscow, 2010) [in Russian].

    Google Scholar 

  7. B. K. Lebedev, “Switch-block routing based on genetic procedures,” Izv. Taganrog Radio Eng. Univ., Dedicated issue on Intelligent CAD Systems, No. 2, 7–21 (1998).

    Google Scholar 

  8. D. S. Knysh and V. M. Kureichik, “A genetic algorithm for switch-block routing,” Izv. Vyssh. Uchebn. Zaved., Elektronika, Skhemotekhnika, Proektirovanie, No. 5(79), 28–34 (2009).

    Google Scholar 

  9. Y.-W. Chang, and S.-P. Lin, “MR: A new framework for multilevel full-chip routing,” IEEE Trans. Comput.—Aided Des., Integr. Circuits Syst. 23, 793–800 (2004).

    Article  Google Scholar 

  10. J. Cong, J. Fang, M. Xie, and Y. Zhang, “Mars—a multilevel full-chip gridless routing system,” IEEE Trans. Comput.-Aided Des., Integr. Circuits Syst. 24, 382–394 (2005).

    Article  Google Scholar 

  11. Tai-Chen Chen and Yao-Wen Chang, “Multilevel full-chip gridless routing with applications to optical-proximity correction,” IEEE Trans. Comput.-Aided Des., Integr. Circuits Syst. 26, 1041–1053.

  12. B. K. Lebedev and E. I. Voronin, “A multilevel approach to full-chip routing using a modification of the ant colony algorithm,” Izv. Izv. Yuzhn. Feder. Univ., Ser. Tekhn. Nauki, No. 7, 73–80 (2011).

    Google Scholar 

  13. T. Yoshimura and E. S. Kuh, “Efficient algorithms for channel routing,” IEEE Trans. Computer Aided Design Integrated Circuits Syst. 1, 25–35 (1982).

    Article  Google Scholar 

  14. X. Liu, A. Sakamoto, and T. Shimamoto, “Restrictive channel routing with evolution programs,” Trans. IEICE, 1(E76-A), 1738–1745 (1993).

    Google Scholar 

  15. V. M. Kureichik, B. K. Lebedev, and V. B. Lebedev, “VLSI floorplanning based on the integration of adaptive search models,” J. Comput. Syst. Sci. Int. 52, 80–96 (2013).

    Article  MATH  Google Scholar 

  16. B. K. Lebedev, V. B. Lebedev, and O. B. Lebedev, “Evolutionary mechanisms in channel routing,” Izv. Izv. Yuzhn. Feder. Univ., Ser. Tekhn. Nauki, No. 9(86), 12–18 (2008).

    Google Scholar 

  17. B. K. Lebedev and V. B. Lebedev, “Chanel routing based on the simulation of adaptive behavior of a swarm of particles in the space of solutions with unordered linguistic scales,” in Intelligent Systems: Collective Monograph (Fizmatlit, Moscow, 2011), pp. 66–84 [in Russian].

    Google Scholar 

  18. V. B. Lebedev, “Channel routing based on the use of bee colony optimization,” in Proc. of the Congress on Intelligent Systems and Information Technologies, AIS-IT’011 (Fizmatlit, Moscow, 2011), Vol. 2, pp. 7–14 [in Russian].

  19. V. B. Lebedev, “Models of the adaptive behavior of a bee colony as applied to graph problems,” Izv. Izv. Yuzhn. Feder. Univ., Ser. Tekhn. Nauki, No. 7(132), 14–22 (2012).

    Google Scholar 

  20. V. B. Lebedev, “Construction of connecting networks based on swarm intelligence and genetic evolution,” in Proc. of the XIVth All-Ruassia Conf. NEIROINFORMATIKA-2012 (Fizmatlit, Moscow, 2012), Part 2, pp. 93–103 [in Russian].

    Google Scholar 

  21. N. Taniguch, X. Liu, A. Sakamoto, and T. Shimomoto, “An approach to channel routing using genetic algorithms,” Bulletin of Faculty of Engineering, Tokio, No. 38, 99–112 (1993).

    Google Scholar 

  22. A. T. Rahmani and N. Ono, “A genetic algorithm for channel routing problem,” in Proc. of the 5th Int. Conf. on Gas, Milan, 1993, pp. 494–498.

  23. V. M. Kureichik and B. K. Lebedev, “A genetic switch-box routing algorithm,” Izv. Vyssh. Uchebn. Zaved., Elektronika, No. 2, 55–66 (2002).

    Google Scholar 

  24. M. Dorigo and T. Stützle, Ant Colony Optimization (MIT Press, Cambridge, 2004).

    Book  MATH  Google Scholar 

  25. S. D. Shtovba, “Ant colony algorithms,” Exponenta Pro, No. 4, 70–75 (2003).

    Google Scholar 

  26. A. A. Kazharov and V. M. Kureichik, “Ant Colony Optimization Algorithms for Solving Transportation Problems,” J. Comput. Syst. Sci. Int. 49, 30–43 (2010).

    Article  MATH  MathSciNet  Google Scholar 

  27. V. M. Kureichik, B. K. Lebedev, and O. B. Lebedev, “A hybrid partition algorithm based on natural decision making mechanisms,” in Artificial Intelligence in Decision Making (Institut sistemnogo analiza RAN, Moscow, 2012), pp. 3–15 [in Russian].

    Google Scholar 

  28. Automated Design of Circuit Boards Electronic Radio Equipment: Handbook, Ed. by L. P. Ryabov (Radio i svyaz’, Moscow, 1986) [in Russian].

    Google Scholar 

  29. T. Yan and M. D. F. Wong, “BSG-route: A length-constrained routing scheme for general planar topology,” in Proc. of the Int. Conf. on Compiuter-Aided Design, New York, 2008, pp. 499–505.

  30. M. M. Ozdal and M. D. F. Wong, “Algorithmic study of single-layer bus routing for high-speed boards,” IEEE Trans. Computer Aided Design Integrated Circuits Syst. 25, 490–503 (2006).

    Article  Google Scholar 

  31. J. Cong, M. Romesis, and M. Xie, UCLA Optimality Study Project, http://cadlab.cs.ucla.edu/~pubbench

  32. MCNC Electronic and Information Technologies, www.mcnc.org

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to B. K. Lebedev.

Additional information

Original Russian Text © V.M. Kureichik, B.K. Lebedev, O.B. Lebedev, 2015, published in Izvestiya Akademii Nauk. Teoriya i Sistemy Upravleniya, 2015, No. 2, pp. 117–133.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kureichik, V.M., Lebedev, B.K. & Lebedev, O.B. Channel routing based on ant colony adaptive behavior model. J. Comput. Syst. Sci. Int. 54, 278–293 (2015). https://doi.org/10.1134/S1064230715020094

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1064230715020094

Keywords

Navigation