计算机工程与应用2019，Vol.55Issue(3)：15-22,8.DOI:10.3778/j.issn.1002-8331.1809-0316
基于聚度的自适应动态混沌蚁群算法
Adaptive Dynamic Chaotic Ant Colony Algorithm Based on Degree of Aggregation
刘明霞 1游晓明 1刘升2
作者信息
- 1. 上海工程技术大学 电子电气工程学院,上海 201620
- 2. 上海工程技术大学 管理学院,上海 201620
- 折叠
摘要
Abstract
Aiming at the problem that the ant colony algorithm is slow in convergence and easily falls into a local opti-mum, an adaptive dynamic chaotic ant colony algorithm(A_ACS)based on the degree of aggregation is proposed. In the early iterations, the degree of aggregation is used to measure the diversity of solutions and self-adaptively adjust the local pheromone distribution, and chaos operators are introduced to increase the diversity of the population to avoid the algo-rithm falling into a local optimum, thereby improving the accuracy of the solution. In the later iterations, the chaotic operator is removed to reduce the chaotic disturbance and increase the convergence speed of the algorithm. The A_ACS is used for the TSP problem. The simulation results show that the proposed algorithm reduces the search time and improves the quality of solution compared with the ACS and MMAS algorithm. It balances the contradiction between diversity and conver-gence, and the overall performance is better than the other two algorithms.关键词
蚁群算法/聚度/混沌优化/自适应信息素更新/旅行商问题Key words
ant colony algorithm/degree of aggregation/chaotic optimization method/adaptive method of updating pheromone/traveling salesman problem分类
信息技术与安全科学引用本文复制引用
刘明霞,游晓明,刘升..基于聚度的自适应动态混沌蚁群算法[J].计算机工程与应用,2019,55(3):15-22,8.
