摘要
提供满足驾驶员多个心理期望的路径是导航系统该解决的关键问题,其本质是资源约束最短路径问题,属于NP难问题,无法使用传统的最短路径算法解决.提供了多约束路径规划的数学模型,并使用了蚁群算法对其求解,在算法中针对问题重新设计了信息素更新规则和启发因子.实验证明算法具备良好的寻优能力,能准确找出路网中满足多种属性约束的路径.
How to provide route to meet the driver＇s muhiple psychological expectations is the key problem of navigation system. The essence of this problem is resource constrained shortest path problem （RCSP）, which belongs to NP-C problems and can not be solved with the traditional shortest path algorithm. Muhi-constrained shortest path mathematical model was presented, and ant colony algorithm was used to solve it. Aimed at the problem, pheromone update rule and heuristic factor were redesigned in the algorithm. Experiments show that the improved optimization algorithm have a good ability to accurately find multi-constrained shortest path in road network.
出处
《湖南科技大学学报（自然科学版）》
CAS
北大核心
2010年第1期87-90,共4页
Journal of Hunan University of Science And Technology：Natural Science Edition
基金
国家自然科学基金资助项目(50978106)
关键词
多约束
路径规划
蚁群算法
multi-constrained
route plan
improved ant colony algorithm
