基于模拟退火的公交调度模型  

Research on Bus Scheduling Model Based on Simulated Annealing

作　　者：曾杰华 王向华 吴广 张飞飞 ZENG Jiehua;WANG Xianghua;WU Guang;ZHANG Feifei(School of Computer Science and Engineering,Hunan University of Information Technology Hunan Province Higher Education Key Laboratory of Intelligent Sensing and Computing,Changsha 410151,China)

机构地区：[1]湖南信息学院计算机科学与工程学院湖南省智能感知与计算重点实验室,长沙410151

出　　处：《交通工程》2024年第10期49-55,共7页Journal of Transportation Engineering

基　　金：2022年度湖南省教育厅科学研究项目“基于情景感知的智慧公交调度模型研究”(项目编号:22C1163)。

摘　　要：为深入了解通用、简洁的公交调度策略,以现存的2013年10月23日深圳市公交导航定位数据为研究对象,运用一次聚类方法找到最近的公交首末站聚点信息和各簇信息。利用实时公交定位数据、公交行驶速度,实时计算各区域公交转移参数H(t),运用模拟退火算法进行短时调度。再扩大到更大区域,计算更为复杂的公交转移参数H(t),采用模拟退火算法对该区域公交速度进行调度,达到降低公交运行费用目的。模拟实验结果表明,采用修正速度后的模拟退火算法比原模型能提升10%以上的运行时间,提高公交运行效率,促进节能减排。In order to gain a deeper understanding of universal and concise bus scheduling strategies,the existing Shenzhen bus navigation and positioning data from October 23,2013 was used as the research object,and a one-time clustering method was applied to find the nearest bus start and end station cluster information and each cluster information.Using real-time bus positioning data and bus travel speed,calculate the transfer parameters H(t)of buses in each region in real time,and use simulated annealing algorithm for short-term scheduling.Expand to a larger area,calculate more complex bus transfer parameters H(t),and use simulated annealing algorithm to schedule bus speeds in the area,in order to reduce bus operating costs.The simulation experiment results show that using the modified speed simulated annealing algorithm can improve the running time by more than 10%compared to the original model,improve the efficiency of public transportation operation,and promote energy conservation and emission reduction.

关 键 词：智能公交系统 聚类分析 python可视化 模拟退火算法 动态调度 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] U491[自动化与计算机技术—控制科学与工程]