Fault-tolerant network computation of individuals in genetic algorithms
Fault-tolerant network computation of individuals in genetic algorithms
复制标题
遗传算法中个体的容错网络计算
DOI：
10.1109/cec.2002.1004502
复制
发表时间：
2002
期刊：
影响因子：
--
通讯作者：
D. Stacey
中科院分区：
文献类型：
--
作者：
A. Hamilton;D. Stacey
许多遗传算法都有复杂的适应度函数，只要有工具，就可以很容易地并行计算。本文探讨了如何使用一种工具从一组可变的机器中收集空闲计算周期，以实现这类遗传算法的收敛。对GAS稳态模型的修改允许我们使用底层瘦网络计算系统的容易出错的行为作为GA本身的噪声。这种“真实的”噪声被合并到GA中，在噪声严重的网络环境中保持收敛的动力。
Many genetic algorithms have complex fitness functions which can easily be calculated in parallel, given the tools to do so. This paper explores the use of a tool to gather spare computing cycles from a variable set of machines to allow convergence of GAs of this type. A modification to the steady-state model for GAs allows us to use the fault-prone behavior of an underlying thin networked computation system as noise within the GA itself. This "real" noise is incorporated into the GA, maintaining the drive towards convergence in the case of the heavily noisy network environment.