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Optimizing Train Network Routing Using Deterministic Search

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Abstract

In this paper, we use walk search strategy to solve the optimization problem of train routing on railway network. The proposed approach is a local search algorithm which explores the railway network by walker’s navigating through the network. Using some selection rules, walker can dynamically determine the optimal route of trains. In order to analyze and evaluate the proposed approach, we present two computational studies in which the search algorithm is tested on a part of railway network. The results demonstrate that the proposed approach is an effective tool for optimizing the train routing problem on railway network. Moreover, it can be executed with shorter computation time.

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Authors and Affiliations

  1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, 100044, People’s Republic of China

    KePing Li, ZiYou Gao, BaoHua Mao & ChengXuan Cao

Authors
  1. KePing Li
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  2. ZiYou Gao
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  3. BaoHua Mao
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  4. ChengXuan Cao
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Corresponding author

Correspondence to KePing Li.

Additional information

The project is supported by National Natural Science Foundation of China under Grant Nos 60634010 and 60776829, New Century Excellent Talents in University under Grant No NCET-06-0074 and the Key Project of Chinese Ministry of Education under Grant No 107007.

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Li, K., Gao, Z., Mao, B. et al. Optimizing Train Network Routing Using Deterministic Search. Netw Spat Econ 11, 193–205 (2011). https://doi.org/10.1007/s11067-009-9098-7

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