Abstract
The problem of circuit partitioning is a key phase in the physical design of VLSI. In this paper, we propose a multi-objective discrete PSO (DPSO) algorithm for the problem of VLSI partitioning. Moreover, a new strategy of heuristic local search is employed to accelerate the convergence. The main target of this multi-objective problem is optimizing the minimum cut and timing performance (delay) while area balance is taken as a constraint. The fitness function of phenotype sharing is used to evaluate solution by both pareto dominance and neighborhood density. The experimental results on ISCAS89 benchmarks are performed to validate the proposed algorithm. Compared with genetic algorithm (GA) and Tabu Search (TS) in literature [4], the proposed algorithm could obtain more markedly better solutions for bipartition problem.
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Peng, Sj., Chen, Gl., Guo, Wz. (2010). A Multi-objective Algorithm Based on Discrete PSO for VLSI Partitioning Problem. In: Cao, By., Wang, Gj., Chen, Sl., Guo, Sz. (eds) Quantitative Logic and Soft Computing 2010. Advances in Intelligent and Soft Computing, vol 82. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15660-1_66
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DOI: https://doi.org/10.1007/978-3-642-15660-1_66
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