An Adaptive Hybrid Genetic Algorithm for VLSI Standard Cell Placement Problem
An Adaptive Hybrid Genetic Algorithm for VLSI Standard Cell Placement Problem
复制标题
DOI：
10.1109/icisce.2016.45
复制
发表时间：
2016-07
期刊：
影响因子：
--
通讯作者：
Xiongfeng Chen;Geng Lin;Jianli Chen;Wen-xing Zhu
中科院分区：
文献类型：
--
作者：
Xiongfeng Chen;Geng Lin;Jianli Chen;Wen-xing Zhu
针对属于NP难组合优化问题的VLSI标准单元布局问题，提出了一种自适应混合遗传算法（AHGA）。根据不同规模和数组或非数组放置方式的问题解空间的特点，我们相应地使用了一些自适应策略来大大减少运行时间。我们在构建单一交叉模因和接受安置候选人的适应性策略上进行了创新。在Peko suite3和ISPD04基准电路上进行了实验测试，结果和比较表明这些策略是有效的。
This paper presents an adaptive hybrid genetic algorithm (AHGA) for VLSI standard cell placement problem which belongs to NP-hard combinatorial optimization problem. Based on the distinguishing feature of solution space of the problems with various scale and array or non-array placement style, we correspondingly use some adaptive strategies to greatly reduce the runtime. We make innovations in the adaptive strategies for constructing single crossover meme and accepting placement candidate. The experimental tests are performed on Peko suite3 and ISPD04 benchmark circuits, the results and comparisons show that these strategies are efficient.