兵工自动化2012，Vol.31Issue(4)：28-31,4.DOI:10.3969/j.issn.1006-1576.2012.04.008
一种基于信息素变化的改进蚁群算法
An Improved Ant Colony Algorithm Based on Pheromone Changing
刘海军 1彭绍雄 2高传斌 1邹强2
作者信息
- 1. 海军航空工程学院研究生管理大队,山东烟台264001
- 2. 海军航空工程学院飞行器工程系,山东烟台264001
- 折叠
摘要
Abstract
The ant colony algorithm search time is long and it is easy to fall into the local optimal. Put forward the amplitude descending local phenomenon renovating model. Through analyzing why the present algorithm fall into the local optimal, and using ant colony recombining algorithm, and according to hypothesis deduce amplitude descending local phenomenon renovating model, and analyze influence of model on algorithm complexity. Then use four pheromone renovating models to solve the shortest path problems. The simulation result shows that the model can restrain the algorithm to fall into the local optimal.关键词
蚁群算法/增幅递减/局部最优/信息素变化Key words
ant colony algorithm/ amplitude descending/ local optimal problem/ growth changing分类
信息技术与安全科学引用本文复制引用
刘海军,彭绍雄,高传斌,邹强..一种基于信息素变化的改进蚁群算法[J].兵工自动化,2012,31(4):28-31,4.
