Freight Railroad Network Blocking Problem: Modeling, Formulation and Improved Particle Swarm Optimization Algorithm

In this paper, we introduce Railroad Blocking Problem (RBP) for network. Then we propose a model formulation and an improved algorithm for RBP. The objective function of the model is to minimize the total time costs of freight trains operation, including trains running time in section, accumulation and resorting time at station. The constraints include resorting capacity of stations, carrying capacity of sections, the balance of flow, etc. To solve the model for real world railroad networks, an improved hybrid Particle Swarm Optimization and Lagrange Relaxation (PSO-LR) algorithm is implemented. Finally, the computation results on a case of simplified China's railroad network demonstrate the effectiveness and validation of the proposed method, which shows the potential application on railroad engineering industry.