基于遗传模拟退火算法的门阵列布局方法

Gate Array Placement Method Based on Genetic Simulated Annealing Algorithm

为实现门阵列模式布局,将遗传算法与模拟退火算法相结合,提出一种新的遗传模拟退火算法,利用遗传算法进行全局搜索,利用模拟退火法进行局部搜索,在进化过程中采用精英保留策略,对进化结果进行有选择的模拟退火操作,既加强了局部搜索能力又防止陷入局部最优。实验结果表明,与传统遗传算法相比,该算法能够有效提高全局搜索能力。

In order to implement gate array mode placement,Genetic Algorithm（GA） is combined with Simulated Annealing（SA） algorithm. A novel GASA algorithm is proposed. The GA is served as the main flow of the new algorithm for global search,while the SA algorithm adjusts local search. In this process,excellent results are retained and simulated annealing,which strengthens capabilities of local search and avoids trapping in the local optimum. Experimental results show that,compared with traditional GA,this algorithm can promote the global search capacity effectively.