一种多策略协同的加速和声搜索算法

被引：3

作者：

李树荣 ^{[1
]}

陈国霞 ^{[2
]}

雷阳 ^{[1
]}

张强 ^{[1
]}

机构：

[1] 中国石油大学(华东)信息与控制工程学院

[2] 中国石化青岛液化天然气有限责任公司

来源：

系统科学与数学 | 2013年 / 33卷 / 10期

关键词：

和声搜索; 混沌扰动; 参数自适应; 聚类分析.;

D O I：

暂无

中图分类号：

TP391.3 [检索机];

学科分类号：

080201 [机械制造及其自动化];

摘要：

基本和声搜索算法的全局搜索能力较强,但局部收敛速度较慢,针对该不足,提出了一种改进方案.在基本和声搜索算法的基础上,采用分阶段优化的思想,在算法迭代的不同阶段分别采取不同的策略改进算法的局部收敛速度.在迭代初期采用混沌策略初始化和声库,在迭代的中后期采用聚类和混沌扰动策略进行加速,在迭代的后期采用停滞混沌变异避免算法陷入局部最优,并在算法的整个迭代过程中对算法参数进行动态自适应.利用5个Benchmark函数对改进算法的性能进行了测试,并与已存在的和声搜索算法进行比较,结果表明了改进算法的有效性.

引用

页码：1144 / 1155

页数：12

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