并行化遗传算法研究综述

被引：154

作者：

冯智莉 ^{[1
]}

易国洪 ^{[1
,2
]}

李普山 ^{[1
]}

黎慧源 ^{[1
]}

代瑜 ^{[1
]}

机构：

[1] 武汉工程大学计算机科学与工程学院

[2] 武汉工程大学智能机器人湖北省重点实验室

来源：

计算机应用与软件 | 2018年 / 35卷 / 11期

关键词：

经典遗传算法; 并行化; 性能评估;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

140502 [人工智能];

摘要：

说明遗传算法的基本思想和特点。根据近五年国内遗传算法的研究现状,分析遗传算法当前发展的潜力与不足。对遗传算法未来的发展和研究热点进行了推理,指出遗传算法的主要发展方向是并行化,研究热点将集中在早熟机理和参数设置等方面,并且遗传算法未来会跟其他的技术进一步结合。从遗传算法的主要环节入手,分析遗传算法的并行化策略和4种常见的并行化模型,并分析不同模型使用的硬件环境和模型的优缺点。对并行化遗传算法的评价模型进行讨论,说明了常见的评价模型和改进之处。

引用

页码：1 / 7+80 +80

页数：8

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