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Topology transformation-based multi-path algorithm for urban rail transit network
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AI
DOI：10.1016/j.trc.2021.103540.png)
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Abstract
En 中文
In the large-scale rail network, it is easy to suffer from the dilemma of inefficiency for existing multi-path algorithms. The majority of research has been devoted to improving the search ability of multi-path algorithms. However, a few investigations focus on simplifying the network, and the research with a rigorous methodology is in early childhood. This study proposes a novel multi-path algorithm with compression network space to search the multiple paths. First, a bi-layer transformation operator is developed to streamline the topology structure of the rail network. Specifically, a first-layer transformation operator employs the station extraction function to simplify the type of stations. After that, a second-layer transformation operator with a path filter function is designed to eliminate the non-effective connection structure. Therefore, a streamlined hierarchical topology network (SHTN) is generated. Sequentially, for the four types of Origin-Destination pairs (ODs), K-shortest paths between an ODs are found by executing four matching mechanisms and the modified Yen's algorithm. Finally, to verify the effectiveness and efficiency, a series of experiments run on the selected Beijing rail network. The results show that the proposed algorithm has obvious superiority or competitiveness over state-of-the-art algorithms.
Keywords:
Multiple paths
Urban rail transit system
Topology transformation
9-intersection model
Streamlined hierarchical topology network
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