Placement constraints and macrocell overlap removal using particle swarm optimization

Authors:
Sheng-Ta Hsieh;Tsung-Ying Sun;Cheng-Wei Lin;Chun-Ling Lin
Affiliations:
Intelligent Signal Processing Lab., Department of Electrical Engineering, National Dong Hwa University, Shoufeng, Hualien, Taiwan, R.O.C.;Intelligent Signal Processing Lab., Department of Electrical Engineering, National Dong Hwa University, Shoufeng, Hualien, Taiwan, R.O.C.;Intelligent Signal Processing Lab., Department of Electrical Engineering, National Dong Hwa University, Shoufeng, Hualien, Taiwan, R.O.C.;Intelligent Signal Processing Lab., Department of Electrical Engineering, National Dong Hwa University, Shoufeng, Hualien, Taiwan, R.O.C.
Venue:
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
Year:
2006

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Abstract

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.