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中文摘要：
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.
英文摘要：
Community shuttle plays an important role in the efficient operation of public transit microcirculation.The optimization of community shuttle routes is also an important work to enable community shuttles to connect rail lines well.This paper defines the potential passenger demand indicators from the view of segments in a given network first,then aims at generating a cyclic route with the objective of maximizing the potential passenger demand,considering the maximum travel time constrain and the characteristics of the cyclic routes.In solving the problem,a set of algorithm for crossover and mutation of route segments is presented,by this a genetic algorithm （GA） can be carried out smoothly to solve the problem as a heuristic algorithm.At last,a case study of Tiantongyuan Community in Beijing is presented.GA and a depth first search （DFS） are both presented to work out the optimal shuttle route serviced for the community based on the passenger count data.The results show that the solution obtained by GA is the optimal route in this case,so GA is feasible in solving this kind of problem.
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