| 摘 要: 针对免疫多目标进化算法分布性欠佳的缺陷，提出一种基于自适应网格方法的免疫多目标进化算法。基 本思想是：对抗体群进行免疫克隆、免疫基因和克隆选择操作后，利用自适应网格方法提高抗体群的多样性。仿真实验 结果和统计指标显示，改进算法与常规免疫多目标进化算法相比较，在解的分布性方面有了较大程度的改进。 |
| 关键词: 多目标进化；人工免疫；自适应网格方法；分布性 |
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中图分类号: TP312
文献标识码: A
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| 基金项目: 安徽省教育厅自然科学基金项目(2016KB246)资助. |
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| An Immune Multi-Objective Evolutionary Algorithm Based on the Adaptive Grid Method |
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LV Wenpeng,XU Feng
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( College of Mathematics and Big Data, Anhui University of Science and Technology, Huainan 232001, China)
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| Abstract: Aiming at the defect of poor distribution in immune multi-objective evolutionary algorithm (IMOEA),an improved IMOEA based on the adaptive grid method is proposed.The basic idea is that after the immune clone,immune gene and clonal selection operation of the antagonism group,the adaptive grid method is adopted to improve the diversity of the antibody population.The results of the simulation experiment and the statistical index show that the improved algorithm has a great improvement in the distribution of the solution compared with the conventional immune multi-objective evolutionary algorithm. |
| Keywords: multi-objective evolution;artificial immune;adaptive grid method;distribution |
