周勇,胡中功

• 1:长江大学工程技术学院信息工程学院
• 2:武汉工程大学电气信息学院

摘要(Abstract)：

遗传算法作为一种模仿生物自然进化过程的全局随机优化算法,在工程中已得到广泛应用。但普通遗传算法易存在早熟及收敛速度慢等缺点。提出一种快速收敛的改进遗传算法,该算法从全局出发,对初始群体生成、遗传选择、交叉和变异算子操作等几个方面做出改进,其中重点对交叉率和变异率进行优化,实现交叉率和变异率按个体适应度以S曲线和高斯分布曲线形式进行非线性自适应调整。通过案例仿真分析,证明了该方法的可行性和有效性,且具有更快的收敛速度和更可靠的稳定性。

关键词(KeyWords)： 遗传算法;高斯分布;自适应;收敛;性能仿真;函数优化

Abstract:

Keywords:

基金项目(Foundation): 云南省教育厅科学研究基金(2016YJS020);; 长江大学工程技术学院科研基金项目(2018ky08)~~

作者(Author): 周勇,胡中功

DOI: 10.16652/j.issn.1004-373x.2018.17.034

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