Placement Constraints and Macrocell Overlap Removal Using Particle Swarm Optimization

  • Sheng-Ta Hsieh
  • Tsung-Ying Sun
  • Cheng-Wei Lin
  • Chun-Ling Lin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4150)


This paper presents a macrocell placement constraints and overlap removal methodology using particle swarm optimization (PSO). The authors adopted several techniques along with PSO as to avoid the floorplanning falling into the local minimum and to assist in finding out the global minimum. Our method can deal with various kinds of placement constraints, and consider them simultaneously. Experiments employing MCNC and GSRC benchmarks show the efficiency and robustness of our method for restricted placement and overlap removal obtained by the ability of exploring better solutions. The proposed approach exhibited rapid convergence and led to more optimal solutions than other related approaches, furthermore, it displayed efficient packing with all the constraints satisfied.


Particle Swarm Optimization Lower Left Corner Very Large Scale Integration Wire Length Global Good Position 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Sheng-Ta Hsieh
    • 1
  • Tsung-Ying Sun
    • 1
  • Cheng-Wei Lin
    • 1
  • Chun-Ling Lin
    • 1
  1. 1.Intelligent Signal Processing Lab., Department of Electrical EngineeringNational Dong Hwa UniversityShoufeng, HualienTaiwan, R.O.C.

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