基于多叉树蚁群算法在区位选址中的应用

【作者】 赵元； 张新长； 康停军；

【机构】 中山大学地理科学与规划学院；

【摘要】 提出了基于多叉树蚁群算法(ant colony optimization based on multiway troe)的区位选址求解方法。在多目标和大型空间尺度约束条件下,地理区位选址的解决方案组合呈现海量规模、空间搜索量庞大,难以求出理想解。基于多叉树的蚁群算法对地理空间进行多叉树划分,在多叉树的层上构造蚂蚁路径(ant path),让蚂蚁在多叉树的搜索路径上逐步留下信息素,借助信息素的通讯来间接协作获得理想的候选解。采用该方法用于广州市的地理区位选址,取得良好结果。实验结果表明:采用基于多叉树的蚁群算法,改善了蚂蚁在空间搜索能力,使大规模空间区域空间选址具有更快的运行和收敛速度。更多还原

【Abstract】 The geographical site selection takes large volume spatial data and contains too many solutions under the constraint condition of multi-objective and spatial raster.Take the suitable heuristic search method has become a pressing problem to improve the spatial search capabilities.In this paper,an improved ant colony optimization based on multiway tree is introduced to solve p-median site location problem.The geographical space is divided by the multiway tree and the ant paths are constructed on the levels divided by multiway tree.The ant can leave the pheromone on the multiway search path,and an ideal solution can be obtained by the construction of pheromone.The results show that the proposed algorithms have better performance in convergence precision and the computing time for solving site search problem.更多还原