摘要
针对复杂地理环境下最短路径寻优问题,文章设计了基于障碍距离的优化算法。算法引入了地表距离、障碍距离等概念,综合考虑了地理空间高程、坡度、障碍物等空间信息,以适合于复杂地形条件下目标间距离计算;在对目标地理空间网络化基础上,通过确定搜索空间、搜索方向、网络弧段权值等,构建完整的网络拓扑关系网;应用遗传算法进行最优线路寻优,最后通过实验验证了算法的可行性。
For the matter of the shortest path optimization problem under complex geographical environment, this paper designed the optimization algorithm based on obstructed distance. The algorithm introduced the concepts of surface distance, obstacle distance, considering the spatial information such as geographic spatial elevation, slope, obstacles and so on, in order to suit for the distance compute between objects under complexity geographical environment. Moreover, it constructed the complete topologic relationship network through determining the searching space, searching direction and the network＇s path weight based on the target geographical spatial networking. Finally, genetic algorithm was applied to the route optimization, and experimental result verified the feasibility of the algorithm.
出处
《测绘科学》
CSCD
北大核心
2014年第2期37-41,68,共6页
Science of Surveying and Mapping
基金
国家自然科学基金项目(41104047)
关键词
地理环境
障碍距离
最优线路
遗传算法
geographical environment
obstructed distance
optimal path
genetic algorithm
