College of Mathematics and Computer Sciences, Fuzhou University, Fuzhou 350108, China; Key Laboratory of Discrete Mathematics with Applications of the Ministry of Education, Fuzhou 350003, China 在期刊界中查找 在百度中查找 在本站中查找
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.
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