摘要
针对基本蚁群算法容易出现早熟和停滞现象的缺点,提出一种动态自适应蚁群算法,通过引入信息素的自适应调整策略,限制信息素范围以及动态增加信息素的局部更新方式,有效抑制收敛过程中的停滞现象,提高算法的搜索能力.该算法的性能在中国旅行商问题(China TravelingSalesman Problem,CTSP)和Eil50问题上得到验证.
A dynamic and adaptive ant colony algorithm is presented in accordance with the defect of early variety and stagnation. The contribution of the algorithm includes an adaptive strategy of pheromone, the limited range of pheromone, and a local updating for pheromone dynamically. This method is able to restrain stagnation during the iteration process effectively, and enhance the capability of search. The experimental results for solving China Traveling Salesman Problem（CTSP） and EilSO are proved to be effective.
出处
《计算机辅助工程》
2006年第4期10-13,18,共5页
Computer Aided Engineering
基金
上海市教育委员会科研项目(05FZ06)
上海海事大学重点学科建设项目(XL0105)
关键词
蚁群算法
组合优化
旅行商问题
ant colony algorithm
combinatorial optimization
traveling salesman problem（TSP）
