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Transit network design with meta-heuristic algorithms and agent based simulation

机译:基于元启发式算法和代理模拟的传输网络设计

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In this work, a transit network design problem is presented. The problem is identified as a typical large-scale complex system. Subsequently, it is decomposed into its sub-components. The first two sub-components, which encompass the network design and frequency setting problems, are then tackled by means of an innovative solution framework that combines a genetic algorithm with agent-based travel demand modelling. An analysis of results obtained from applying the proposed method to different testing scenarios shows that it is capable of designing transit networks that address the individual and collective perspectives of different stakeholders. Hence it can be used as a viable decision support tool for policy makers in the transportation network sector.
机译:在这项工作中,提出了过境网络设计问题。问题被标识为典型的大规模复杂系统。随后,它被分解成其子组分。然后,通过创新的解决方案框架来解决一种包含网络设计和频率设定问题的前两个子组件,该框架将遗传算法与基于代理的旅行需求建模相结合的创新解决方案框架。对不同测试场景的应用方法获得的结果显示,它能够设计解决不同利益相关者的个人和集体观点的过境网络。因此,它可以作为运输网络领域的决策者作为可行决策支持工具。

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