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Bus Network Design Using Genetic Algorithm

机译:遗传算法的公交网络设计

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The bus network design problem is an important problem in transportation planning. It is the problem of determining a network of bus lines which best achieves a predetermined objective. This may be done with or without the presence of rapid transit lines. This study is devoted to solving this problem using genetic algorithm. The fitness function is defined as the benefit to the users of the bus network less the cost of the operator of the network, which is to be maximized subject to constraints that properly distribute bus routes over the study area. Objective function calculation depends on the basic data of the city and its bus lines and does not need traffic assignment results. So, it is calculated quickly and it makes the genetic algorithm operation faster. Several good solutions were generated through a sensitivity analysis by changing the parameters of the problem affecting bus route geographical distribution. A network assignment problem was solved for each of the alternative bus networks and several measures of effectiveness were evaluated for them. A multi-objective analysis (concordance analysis) was performed based on 10 measures of effectiveness and 14 weighting systems. As a result, a bus network was proposed for the city of Mashad, Iran.
机译:公交网络设计问题是交通规划中的重要问题。确定最佳地实现预定目标的总线网络的问题。可以在有或没有快速运输线的情况下完成此操作。这项研究致力于使用遗传算法解决这个问题。适应度函数的定义是:给公交网络用户带来的好处,减去网络运营商的成本,要在研究区域内正确分配公交路线的约束条件下使其最大化。目标函数的计算取决于城市及其公交线路的基本数据,不需要交通分配结果。因此,它可以快速计算,从而使遗传算法的运算速度更快。通过更改影响公交路线地理分布的问题的参数,通过敏感性分析产生了一些好的解决方案。解决了每个备用总线网络的网络分配问题,并对其有效性进行了评估。基于10个有效性度量和14个权重系统进行了多目标分析(一致性分析)。结果,提出了到伊朗马沙德市的公共汽车网络。

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