A Genetic Algorithm for VLSI Floorplanning

  • Christine L. Valenzuela
  • Pearl Y. Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1917)


We present a genetic algorithm (GA) which uses a normalized postfix encoding scheme to solve the VLSI floorplanning problem. We claim to have overcome the representational problems previously associated with encoding postfix expressions into GAs, and have developed a novel encoding system which preserves the integrity of solutions under all the genetic operators. Optimal floorplans are obtained for module sets taken from some MCNC benchmarks. The slicing tree construction process, used by our GA to generate the floorplans, has a run time scaling which compares very favourably with other recent approaches.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    D.J. Cavicchio. Adaptive search using simulated evolution. Unpublished doctorial dissertation, University of Michigan, Ann Arbor, 1970.Google Scholar
  2. 2.
    J.P. Cohoon, S.U. Hedge, W.N. Martin and D.S. Richards. Distributed Genetic Algorithms for the Floorplan Design Problem, IEEE Transactions on Computer Aided Design, Vol. 10, No. 4, pages. 483–492, April 1991.CrossRefGoogle Scholar
  3. 3.
    J.H. Holland. Adaptation in natural and artificial systems. Ann Arbor: The University of Michigan Press, 1975.Google Scholar
  4. 4.
    H. Murata and Ernest S. Kuh. Sequence-pair based placement method for hard/soft/pre-placed modules, International Symposium on Physical Design, pages 167–172, 1998.Google Scholar
  5. 5.
    S. Nakatake, H. Murata, K. Fujiyoushi and Y. Kajitani. Rectangle-packing-based module placement, Proceedings IEEE International Conference on Computer-Aided Design, pages 143–145, 1995.Google Scholar
  6. 6.
    S. Nakatake, K. Fujiyoshi, H. Murata and Y. Kajitani. Module Placement on BSG-Structure and IC Layout Applications, Proceedings IEEE International Conference on Computer-Aided Design, pages 484–491, 1996.Google Scholar
  7. 7.
    I.M. Oliver, D.J. Smith, and J.R.C. Holland. A study of permutation crossover operators on the traveling salesman problem. Genetic Algorithms and their Applications: Proceedings of the Second International Conference on Genetic Algorithms, pages 224–230, 1987.Google Scholar
  8. 8.
    V. Schnecke. and O. Vornberger. Genetic Design of VLSI-Layouts, The First International Conference in Genetic ALgorithms in Engineering Systems: Innovations and Applications (GALESIA), IEE, pages 430–435, 1995.Google Scholar
  9. 9.
    L. Stockmeyer. Optimal Orientations of Cells in Slicing Floorplan Design, Information and Control, Vol. 59, pages 91–101, 1983.CrossRefGoogle Scholar
  10. 10.
    G. Syswerda. Uniform Crossover in Genetic Algorithms, Proceedings of the Third International Conference on Genetic Algorithms. Hillsdale, NJ: Lawrence Erlbaum Associates, 1989.Google Scholar
  11. 11.
    Christine L. Valenzuela and Pearl Y. Wang. VLSI Placement and Area Optimization Using a Genetic Algorithm to Breed Normalized Postfix Strings. (Manuscript submitted for publication).Google Scholar
  12. 12.
    D.F. Wong and H.W. Leong and C.L. Liu. Simulated Annealing for VLSI Design, Kluwer Academic Publishers, Norwell, Massachusetts”, 1988.zbMATHGoogle Scholar
  13. 13.
    F.Y. Young and D.F. Wong. How Good are Slicing Floorplans, The VLSI Journal, Vol. 23, pages 61–73, 1997.zbMATHCrossRefGoogle Scholar
  14. 14.
    F.Y. Young and D.F. Wong. Slicing floorplans with pre-placed modules. Proceedings IEEE International Conference on Computer-aided Design, pages 252–258, 1998.Google Scholar
  15. 15.
    F.Y. Young and D.F. Wong. Slicing floorplans with boundary constraints. IEEE Asia South Pacific Design Automation, pages 17–20, 1999.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Christine L. Valenzuela
    • 1
  • Pearl Y. Wang
    • 2
  1. 1.Department of Computer ScienceCardiff UniversityCardiffUK
  2. 2.Department of Computer Science MS4A5George Mason UniversityFairfaxUSA

Personalised recommendations