A distributed parallel genetic local search in distributed computing environments
A distributed parallel genetic local search in distributed computing environments
复制标题
分布式计算环境中的分布式并行遗传局部搜索
DOI：
10.1109/cec.2003.1299811
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
T. Matsumura
中科院分区：
文献类型：
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作者：
Y. Gong;Morikazu Nakamura;T. Matsumura
提出了一种分布式环境下不规则拓扑遗传局部搜索的并行分布式计算方法。我们提出的方案是实现与树网络拓扑结构，每个计算单元进行遗传本地搜索自己的染色体集和通信时，每一代的最佳解决方案是改善与它的父母。我们评估所提出的算法在PC集群上实现的网格模拟环境。在星星、线、平衡二叉树和边二叉树四种拓扑结构上对算法进行了测试，发现拓扑结构的深度和独立搜索节点的数目对算法的演化过程有影响。此外，我们在实验中观察到的“重置”机制的人口收敛后，是如此有用的网格计算环境。
We propose a parallel and distributed computation of genetic local search with irregular topology in distributed environments. The scheme we propose is implemented with tree network topologies where each computing element carries out genetic local search on its own chromosome set and communicates with its parent when the best solution of each generation is improved. We evaluate the proposed algorithm in a grid simulation environment implemented on a PC-cluster. We test our algorithm on four types topologies: star, line, balanced binary tree and sided binary tree, and find that the topology's depth and the number of independent search nodes influences on the evolution process. Furthermore, we observe in the experiment 'Reset' mechanism of the population after convergence is so useful in grid computing environments.