社区公交接驳地铁路径优化研究

发布时间：2018-10-31 11:19

【摘要】：社区公交在公共交通运输服务体系中起着重要的微循环作用,其路径的优化问题对于出行者及运营企业均具有重要意义.本文在给定的路网条件下,首先从路段角度定义了路段的需求潜力指标,并以最大化路径需求潜力为目标建立目标函数,并兼顾路径旅行时间及圈点线路约束建立了求解一条圈点线路的数学模型.在求解过程中,本文设计了一套路段交叉变异算法并利用遗传算法实现了模型的启发式求解.最后,本文以北京天通苑社区为例,利用该社区居民的出行数据并分别应用遗传算法及深度优先搜索算法对服务于该社区的公交路径进行优化设计.实验结果表明,遗传算法在该实例中已得到最优解,证明遗传算法在求解该问题上具备可行性.
[Abstract]:Community public transport plays an important role in the service system of public transportation, and the optimization of its path is of great significance to both travelers and operators. Under the given road network condition, this paper first defines the demand potential index of road section from the point of view of road section, and establishes the objective function with the aim of maximizing the path demand potential. A mathematical model for solving a loop point line is established by taking into account the path travel time and the loop point line constraints. In the process of solving the problem, a set of cross-mutation algorithm is designed and the heuristic solution of the model is realized by genetic algorithm. Finally, this paper takes the Tiantongyuan community in Beijing as an example, using the travel data of the residents in the community and applying genetic algorithm and depth first search algorithm to optimize the public transport path serving the community. The experimental results show that the genetic algorithm has obtained the optimal solution in this example. It is proved that the genetic algorithm is feasible in solving the problem.
【作者单位】：北京交通大学城市交通复杂系统理论与技术教育部重点实验室;
【基金】：国家自然科学基金(71131001-2) “973”国家重点基础研究发展计划(2012CB725403-5) 北京交通大学优秀博士生科技创新基金资助项目(2013YJS045)
【分类号】：U121

【共引文献】