A decision optimization method for emergency maintenance of regional rail transit based on genetic algorithm

Abstract

Regional rail transit is a comprehensive rail transit system with multiple standards that is formed to meet the needs of urban agglomeration economic integration. The combination of multiple standards makes the road network larger in scale and more complex, so its safety guarantee and emergency maintenance are facing greater challenges. On the one hand, the possibility of multiple concurrent failures/accidents and their overall impact on the road network increase; on the other hand, emergency maintenance resources cannot be invested indefinitely, and reasonable configuration is required. Therefore, how to optimize the emergency maintenance decision for concurrent failures of the road network under the condition of limited emergency maintenance resources has become an important issue that needs to be considered. In response to this problem, this paper proposes a genetic algorithm-based regional rail transit emergency maintenance decision-making optimization method, and establishes a maintenance decision-making optimization mathematical model with the lowest overall transport capacity risk of the road network as the optimization goal. The genetic algorithm is used to solve the optimization mathematical model, and the verification based on simulation example is carried out in conjunction with the rail transit network in the Chengdu-Chongqing area. The verification results show that compared with the commonly used shortest path rescue resource scheduling method, this method can reduce the transport capacity risk of the road network by about 10.37%.