摘要
蚁群算法是一种新的随机优化算法,它利用人工蚂蚁在其途经路上释放信息素寻优,体现了正反馈、分布式、多anent协同性和并行性等特点,蚁群算法中的各参数对计算结果有很大影响.介绍了蚁群算法原理和模型(以TSP问题为例),对基本蚁群算法参数的合理选取进行了实验分析,给出了算法参数选取的基本原则,有利于蚁群算法在优化问题中的应用.
Ant Colony Algorithm is a new stochastic optimization algorithm using artificial ants releasing pheromone on the path, characterized with a positive feedback, distributed computation, multi agent synergy and parallel algorithm. The parameters have an important role in the result of ant colony algorithm. The principle and model of Ant Colony Algorithm were introduced and reasonable experiments were carried out on the parameters of this algorithm, including basic principles for the parameter selection, which are beneficial to the application and development of the ant colony algorithm in optimization problems.
出处
《山东理工大学学报（自然科学版）》
CAS
2008年第1期7-11,共5页
Journal of Shandong University of Technology:Natural Science Edition
基金
国家自然科学基金资助项目(50465001)
山东省中青年科学家奖励基金(2006BS05008)
关键词
蚁群算法
信息素
组合优化
旅行商问题
ant colony algorithm
pheromone
combinatorial optimization
TSP（traveling salesman problem）
