摘要
针对分布估计算法在问题求解过程中容易陷入局部最优的缺点,引入物理退火的思想,提出模拟退火的分布估计算法,其中退火温度以信息熵表示。然后以此为基础,面向多核处理器提供的并行计算能力,提出多量子分布估计的协同优化算法。仿真实验表明,该算法缩短了优化时间,提高了优化结果。
For that EDA is easy to fall in local optimum in the process of problem solving,the physical annealing is introduced into this algorithm and the Simulated Annealing Estimation of Distribution algorithm（SAEDA） is put forward,annealing temperature denoted by information entropy.Afterward,based on this, for parallel compute ability proved by multi-core processor, a quantum-behave estimation of distributions cooperative optimization algorithm is put forward.The simulation experiment result shows that the algorithm can shorten optimize time and improve optimize result.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第26期28-30,98,共4页
Computer Engineering and Applications
关键词
分布估计算法
物理退火
信息熵
协同优化
estimation of distribution algorithm
physical annealing
information entropy
cooperative optimization
