摘要
随着服务产业的快速增长,每逢假期各个旅游景点都成为了度假胜地。越来越多的人喜欢自驾前往旅游景点,如果想自驾去多个景点,如何规划旅游路线让旅游路径花费的时间最短成为了一个难题。粒子群优化算法具有收敛速度快、参数少、算法简单易实现的优点,通过不断迭代更新找到最优解。利用粒子群优化算法对江西的13个5A级景区进行了路径规划。通过百度拾取坐标系统获得景点经纬度坐标,进一步转换为距离进行计算,从而得出途径13个旅游景点的最短路径,并把导航的真实距离作为实验结果。通过实例证明,粒子群优化算法在解决路径优化这类问题上的有效性。
With the rapid growth of the service industry,every holiday season various tourist attractions have become vacation destinations.More and more people like to drive to tourist attractions,and if they want to drive to multiple attractions,how to plan the travel route so that the travel path takes the shortest time becomes a challenge.Particle swarm optimization algorithm has the advantages of fast convergence,few parameters,simple and easy to implement algorithm,and find the optimal solution through continuous iterative update.Path planning for 135A scenic spots in Jiangxi using particle swarm optimization algorithm.The longitude and latitude coordinates of the attractions are obtained through the Baidu pickup coordinate system and further converted into distances for calculation,so as to derive the shortest paths through 13 tourist attractions,and the real distance of navigation is taken as the experimental result.The effectiveness of the particle swarm optimization algorithm in solving such problems as path optimization is demonstrated by examples.
作者
宋艳艳
李广宏
朱玲
夏传林
郑巍
Song Yanyan;Li Guanghong;Zhu Ling;Xia Chuanlin;Zheng Wei(School of Tourism and Landscape Architecture,Guilin University of Technology,Guilin 541000,China;School of Mathematics and Information Science,Nanchang Hangkong University,Nanchang 330063,China;School of Software,Nanchang Hangkong University,Nanchang 330063,China)
出处
《现代计算机》
2023年第11期28-32,共5页
Modern Computer
基金
国家自然科学基金项目(61867004)。
关键词
粒子群算法
路径规划
江西景点
particle swarm optimization algorithm
path planning
Jiangxi attractions
