Rational Selection of Rail Transit Emergency Site Using Complex Network Topology and Genetic Algorithm

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.