摘要
为解决校园资源合理分配,优化校园公交系统运营模式,满足师生日常便捷出行,提出了一种基于0-1整数规划模型的校园公交系统优化方案。该方案以桂林电子科技大学为例,首先对学生的出行现状进行调查,调查结果表明大部分学生都有使用校园公交的意愿,说明校园公交具有一定的发展前景。通过实地测量并收集相关地理数据,使用0-1整数规划对公交站点进行选址,运用蚁群算法优化公交路线,为了解校园公交系统的运载能力进行了仿真模拟实验。最后得到19个公交站点的分布位置和公交最优路线产生的路线长度为4805m,在车辆行驶速度为20km/h以内的限制下,至少需要安排15辆车才可以满足大多数学生时间上的需求。实验结果表明,优化后的校园公交系统规划更加合理,能满足大部分学生的出行需求,适用于中小型校园交通路线规划。
To solve the reasonable allocation of campus resources,optimize the operation mode of the campus public transportation system,and meet the daily convenient travel of teachers and students,an optimization scheme of campus bus system based on 0-1 integer programming model was proposed.The study took Guilin University of Electronic Technology as an example,firstly,the present situation of student travel was investigated,the result shows that most students are willing to use campus bus,which means campus bus has certain development prospects.Through field measurement and collection of relevant geographical data,0-1 integer planning was used to select the location of bus stops and ant colony algorithm was applied to optimize bus routes,and made a series of simulation experiments to test the carrying capacity of the campus bus system.Finally,it was concluded that the distribution location of 19 bus stations and the loop length generated by the optimal bus route is 4805 meters,and under the restriction of the vehicle driving speed within 20km/h,at least 15 buses should be arranged to meet the time needs of most students.The results show that the optimized campus bus system planning is more reasonable,which meets the travel needs of most teachers and students and is suitable for small and medium-sized campus traffic route planning.
作者
魏睿
李凤媛
李科赞
葛志金
WEI Rui;LI Fengyuan;LI Kezan;GE Zhijin(School of Mathematics and Computing Science,Guilin University of Electronic Technology,Guilin 541004,China)
出处
《桂林电子科技大学学报》
2022年第3期223-228,共6页
Journal of Guilin University of Electronic Technology
基金
广西大学生创新训练计划(201910595173)。
关键词
校园公交
0-1整数规划
蚁群算法
站点选址
路线优化
仿真模拟实验
campus bus
0-1 integer programming
ant colony algorithm
site selection
route optimization
simulation experiment
