Hybrid particle swarm optimization algorithm for VLSI circuit partitioning

作者：Guo Wen Zhong; Chen Guo Long^*; Xiong Naixue; Peng Shao Jun

来源：Journal of Software, 2011, 22(5): 833-842.

DOI：10.3724/SP.J.1001.2011.03980

• Benchmark circuit
• Circuit partitioning
• Combinatorial optimization problems
• Hybrid particle swarm optimization algorithm
• Local optima
• Min-cut
• Mutation operators
• Mutation strategy
• NP-hard
• Particle swarm
• Physical design
• Two-point
• Very large scale integration circuit
• Very large-scale integration

Circuit partitioning is an important part of any very large scale integration (VLSI) physical design automation, but it is a NP-hard combinatorial optimization problem. In this paper, a hybrid particle swarm optimization algorithm with FM strategy is proposed to approch this problem. Inspired by the mechinism of genetic algorithm (GA), two-point crossover and random two-point exchange mutation operators have been designed to avoid generating infeasible solutions. To improve the ability of local exploration, FM strategy is applied to the proposed algorithm to update its position. A mutation strategy is also built into the proposed algorithm to achieve better diversity and break away from local optima. Experiments on ISCAS89 benchmark circuits show that the proposed algorithm is efficient. ? 2011 ISCAS.

• 出版日期2011
• 单位福州大学