一种基于熵的OBDD变量排序算法  

An Entropy-based Algorithm for OBDD Variable Ordering

作　　者：赵岭忠[1] 王雪松[1] 古天龙[1] 钱俊彦[1] 

机构地区：[1]桂林电子科技大学计算机系,桂林541004

出　　处：《计算机科学》2007年第2期216-219,共4页Computer Science

基　　金：国家自然科学基金(No.60563005);广西科学基金(0542036)

摘　　要：有序二叉决策图(OBDD)是一种有效表示布尔函数的数据结构,其大小依赖于所采用的变量序。熵是定量描述布尔函数中变量重要性的一种方法。基于变量的熵值分析了高质量变量序的特征,给出了一种基于熵的OBDD变量排序算法。实验结果表明:该算法与模拟退火算法和遗传算法结果相当,时间仅为相应算法的80.84%和29.79%。Ordered binary decision diagrams （OBDDs） are a data structure for efficient representation and manipulation of Boolean functions. The size of OBDDs is very sensitive to variable ordering. Based on the characterization of a variable with its entropy, a property of good variable orders is discovered. An entropy-based method for OBDD variable ordering is proposed. Compared with simulated annealing algorithm and genetic algorithm, the algorithm yields compara ble OBDDs size with an average of 80. 84% and 29.79% runtime, respectively.

关 键 词：有序二叉决策图 变量序 熵 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]