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Conclusion

  • Carl Sechen
Chapter
  • 76 Downloads
Part of the The Kluwer International Series in Engineering and Computer Science book series (SECS, volume 54)

Summary

The use of the simulated annealing algorithm enabled the development of automatic placement and global routing algorithms which performed significantly better than a wide variety of other automatic and manual methods. Also, the algorithms based on simulated annealing captured many of the basic requirements and flexibility demanded by industrial layout problems.

Keywords

Simulated Annealing Simulated Annealing Algorithm Target Node Cell Placement Placement Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    A. Sangiovanni-Vincentelli, Private Communication, (1986).Google Scholar
  2. 1.
    A. Casotto, F. Romeo, and A. Sangiovanni-Vincentelli, “A Parallel Simulated Annealing Algorithm for the Placement of Macro-Cells,” (1987).Google Scholar
  3. 2.
    S. Kravitz and R. Rutenbar, “Placement by Simulated Annealing on a Multiprocessor,” (1987).Google Scholar
  4. 3.
    P. Banerjee and M. Jones, “MA Parallel Simulated Annealing Algorithm for Standard Cell Placement on a Hypercube Computer,” (1986).Google Scholar
  5. 4.
    S. Devadas and R. Newton, “Topological Optimization of Multiple-Level Array Logic,” (1987).Google Scholar
  6. 1.
    A. Casotto, F. Romeo, and A. Sangiovanni-Vincentelli, “A Parallel Simulated Annealing Algorithm for the Placement of Macro-Cells,” (1986).Google Scholar
  7. 1.
    P. Raghavan and C. Thompson, “Probably Good Routing in Graphs: Regular Arrays,” (1985).Google Scholar
  8. 2.
    A. Ng, P. Raghavan, and C. Thompson, “Experimental Results for a Linear Program Global Router,” (1987).Google Scholar

Copyright information

© Kluwer Academic Publishers, Boston 1988

Authors and Affiliations

  • Carl Sechen
    • 1
  1. 1.Yale UniversityUSA

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