摘要
本文在深入分析现有人工免疫算法模型优缺点的基础上,提出了一种基于免疫记忆机制的改进人工免疫算法模型ARTIA.该模型融合了由生物免疫系统启发而来的免疫记忆机制,包括联想记忆和迭代记忆两种,采用了多种策略以保持群体多样性,进而在数值试验的基础上对ARTIA算法模型的性能进行了分析和讨论.最后通过本质上可以归结为旅行商问题(TSP)的多目标组合优化工程实例——岩石钻孔机路径选择问题,验证了该算法的有效性.结论部分对全文作了总结并对今后研究工作进行了展望.
In view of the merits and deficiencies of temporal algorithmic models of artificial immune system (AIS), an improved algorithmic model of AIS based on immunological memory - AKTIA, is proposed, which combines the characteristics of two types of memory viz . Cross - Reactive memory and Iterative memory inspired from the biological immune system. Adopting several strategies to enhance the versatility of population, the behavior of ARTIA model is analyzed and discussed through some numerical experiments . Consequently , the ARTIA algorithm is implemented on an engineering application of path planning of drilling machine that can be viewed as two typical multi-objective combinatorial optimization problems (TSP), the result of which shows the effectiveness of the improved algorithmic model of ARTIA. Some conclusions are reached based on the numerical experiments and the engineering application. Finally, some perspectives on future researches are also made.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2002年第4期385-391,共7页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金(No.70150001)
