【摘要】 <正> 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,为研究人员提供了更多还原

【Abstract】 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.更多还原