计算机应用研究2012，Vol.29Issue(6)：2058-2060,3.DOI:10.3969/j.issn.1001-3695.2012.06.013
一种新的基于logistic混沌映像的自适应混沌蚁群优化算法求解动态车辆路径问题
New ant colony optimization algorithm based on logistic chaotic image to resolve VRP problem
摘要
Abstract
For vehicle routing problem( VRP), this paper proposed a new ant colony optimization algorithm CACO( ACO with chaos image). Put a strong local search ability chaos function ogistic)into the local pheromone update of ant colony algorithm. Made use of the ergodicity feature, randomness feature and regularity feature of chaotic motion to resolve the ASO easy-to-stagnalion phenomenon, improved the algorithm veracity. Selected the standard VRP library for simulation tests to resolve the VRP problem, the new algorithm can find the optimal solution that is known. Compared with other algorithms, it proves the effectiveness of the new algorithm.关键词
logistic混沌映像/局部信息素更新/车辆路径问题Key words
logistic chaotic image/local pheromone update/VRP分类
信息技术与安全科学引用本文复制引用
徐洪丽,钱旭,岳训,马长安,刘康..一种新的基于logistic混沌映像的自适应混沌蚁群优化算法求解动态车辆路径问题[J].计算机应用研究,2012,29(6):2058-2060,3.基金项目
作物生物学国家重点实验室2009年开放课题(2009KF03) （2009KF03）
国家教育部重点资助项目(107021) （107021）
