并行遗传/模拟退火混合算法及其应用  

Parallel Genetic Algorithm / Simulated Annealing Hybrid Algorithm and its Applications

作　　者：温平川[1] 徐晓东[1] 何先刚[1] 

机构地区：[1]重庆邮电学院,重庆400065

出　　处：《计算机科学》2003年第3期86-89,共4页Computer Science

基　　金：重庆市应用基础基金(D2000-02)

摘　　要：1 引言人们常常应用随机优化方法,例如:遗传算法GA(Genetic Algorithms),模拟退火算法SA(Simulated Annealing),爬山算法HC(Hill Climbing),Tabu算法等,解决复杂的非线性函数优化问题。这些方法通常需要大量的计算,从而导致运行时间开销较大。随着计算机及网络技术的高速发展,在高性能计算平台上并行化随机优化方法成为当今研究领域的热门。特别是Beowulf PCs Cluster技术的成熟。This paper presents a highly hybrid Genetic Algorithm / Simulated Annealing algorithm. This algorithm has been successfully implemented on Beowulf PCs Cluster and applied to a set of standard function optimization problems. From experimental results, it is easily to see that this algorithm proposed by us is not only effective but also robust.

关 键 词：混合算法 并行遗传算法 模拟退火算法 随机优化算法 计算机 

分 类 号：O242.23[理学—计算数学] TP301.6[理学—数学]