曹国刚;曹聪;

• 1:上海应用技术大学计算机科学与信息工程学院

摘要(Abstract)：

差异进化算法在解决复杂问题时有着独到的优势,其算法也在不断被改进,但大部分改进算法只利用了搜索空间或适应度空间的单一信息。基于距离选择和适应度排序,提出一种改进的变异选择方法,将部分个体的选择通过综合个体间距离和适应度排序信息得到,该方法改变了经典差异进化算法的变异步骤,可以直接融入常用变异策略中。使用CEC 2017超多目标优化竞赛提供的函数集,从邻近组比例和问题维度对算法的性能影响进行分析和实验,结果表明,邻近组比例与变异策略中的扰动个数有关,最优邻近组比例下的改进算法比已有算法具有更好的运算能力,并且问题越复杂优势越明显。

关键词(KeyWords)： 差异进化;智能选择;变异操作;距离选择;适应度排序;变异策略;优化算法

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金资助项目（41671402）;; 上海市联盟计划项目（LM201811）;; 上海应用技术大学协同创新基金（XTCX2019-14）

作者(Author): 曹国刚;曹聪;

Email:

DOI: 10.16652/j.issn.1004-373x.2021.07.024

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