Abstract
Rail transit network is a convenient and reliable transportation mode in urban areas. With every surge in transportation demand, the network undergoes operational changes like restructuring and making of multiline tracks. Urban rail transit network is a complex network and needs proper emergency services and controlling mechanisms. Unexpected mishaps in rail transit will cause more hazard and panic than the other transportation systems. Therefore, a reliable emergency service station is required to ensure the safety and security of passengers. In the proposed method, the basic statistical properties of complex network topology are considered to construct a P-center site selection model for urban rail transit emergency service stations. The P-center site selection model is solved by genetic algorithm. Validity and reasonableness of the model are demonstrated by implementing it in the Hangzhou emergency service stations for rail transportation. The results show that the P-center site selection model based on statistical properties of complex network topologies can better solve the urban rail transit emergency service station site selection problems. The model minimizes the number of emergency service stations while satisfying the optimal objective function and reduces the construction cost of emergency service stations. The approach has a significant effect on improving system reliability and reducing the risk of emergencies.
Highlights
At present, urban rail transit is in a period of rapid development, strategic development, and management transition.e scale of line network size of major cities continues to expand. e benefits of network scale are becoming increasingly apparent as the challenges of security management increase
Model Solving. e shortest distance between urban rail stations can be solved using Floyd algorithm. e algorithm is implemented through MATLAB programming. e indicators such as degree value and betweenness centrality can be solved by the equation, which is implemented by the PAJEK software. e P-center problem of emergency rescue service siting belongs to nondeterministic polynomial (NP) problem, and the model can be solved by a heuristic algorithm-genetic algorithm. e heuristic algorithm-genetic algorithm can be implemented
Urban rail transit system has become an essential mean of transportation and dispatching
Summary
Received 9 November 2021; Revised 5 January 2022; Accepted 15 January 2022; Published 24 February 2022. Rail transit network is a convenient and reliable transportation mode in urban areas. Urban rail transit network is a complex network and needs proper emergency services and controlling mechanisms. Erefore, a reliable emergency service station is required to ensure the safety and security of passengers. The basic statistical properties of complex network topology are considered to construct a P-center site selection model for urban rail transit emergency service stations. E P-center site selection model is solved by genetic algorithm. Validity and reasonableness of the model are demonstrated by implementing it in the Hangzhou emergency service stations for rail transportation. E results show that the P-center site selection model based on statistical properties of complex network topologies can better solve the urban rail transit emergency service station site selection problems. Validity and reasonableness of the model are demonstrated by implementing it in the Hangzhou emergency service stations for rail transportation. e results show that the P-center site selection model based on statistical properties of complex network topologies can better solve the urban rail transit emergency service station site selection problems. e model minimizes the number of emergency service stations while satisfying the optimal objective function and reduces the construction cost of emergency service stations. e approach has a significant effect on improving system reliability and reducing the risk of emergencies
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