旅游区人群导游最优路径规划仿真研究
发布时间：2019-05-15 15:24
【摘要】：对旅游区人群导游的最优路径规划,可有效提高旅游期间时间的利用率。对导游最优路径进行规划,需要对目标函数进行求解,计算出游览起始点至目的景点的游览路线,完成最优路径的规划。传统方法对规划行为进行分析,建立旅游区最优人群局部动态规划的运动代价评估函数,但忽略了对评估函数求解,导致规划精度低。提出基于蚁群算法的旅游区最优人群导游路径规划模型。依据影响旅游区最优人群导游规划的主要因素建立导游最优路径规划曲折程度约束,给出导游路径规划时间约束、导游路径总长约束,对目标函数进行求解,计算出旅游人群游览起始点至目的景点的游览路线,以此为依据完成对旅游区最优人群导游路径规划。实验结果表明,所提模型及最优路径规划算法给出的路径规划结果更为优化,具有较少的游览规划距离和较为紧凑的游览过程安排。
[Abstract]:The optimal path planning of the tourist guide in the tourist area can effectively improve the utilization rate of the time during the tour. The optimal path of the guide is planned, the objective function needs to be solved, the tour route of the tour starting point and the destination is calculated, and the planning of the optimal route is finished. In the traditional method, the planning behavior is analyzed, and the motion cost evaluation function of the local dynamic programming of the optimal population in the tourist area is established, but the solution of the evaluation function is ignored, and the planning accuracy is low. The paper presents an ant colony algorithm-based tour guide path planning model. according to the main factors that influence the guide planning of the optimal crowd of the tourist area, the guide optimal path planning and winding degree constraint is established, the guide path planning time constraint and the guide path total length constraint are given, and the objective function is solved, And the tour route of the tour start point and the destination scenic spot is calculated, so that the guide path planning of the optimal crowd of the tourist area is completed according to the completion. The experimental results show that the proposed model and the optimal path planning algorithm are more optimized, with less travel planning distance and more compact tour schedule.
【作者单位】： 重庆师范大学涉外商贸学院;
【分类号】：F592.6;TP18
本文编号：2477602
[Abstract]:The optimal path planning of the tourist guide in the tourist area can effectively improve the utilization rate of the time during the tour. The optimal path of the guide is planned, the objective function needs to be solved, the tour route of the tour starting point and the destination is calculated, and the planning of the optimal route is finished. In the traditional method, the planning behavior is analyzed, and the motion cost evaluation function of the local dynamic programming of the optimal population in the tourist area is established, but the solution of the evaluation function is ignored, and the planning accuracy is low. The paper presents an ant colony algorithm-based tour guide path planning model. according to the main factors that influence the guide planning of the optimal crowd of the tourist area, the guide optimal path planning and winding degree constraint is established, the guide path planning time constraint and the guide path total length constraint are given, and the objective function is solved, And the tour route of the tour start point and the destination scenic spot is calculated, so that the guide path planning of the optimal crowd of the tourist area is completed according to the completion. The experimental results show that the proposed model and the optimal path planning algorithm are more optimized, with less travel planning distance and more compact tour schedule.
【作者单位】： 重庆师范大学涉外商贸学院;
【分类号】：F592.6;TP18
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