Optimization of the Sino-Europe Transport Networks Under Uncertain Demand

This paper studies a consolidation center selection and cargo transportation optimization problem of the Sino-Europe railway express. It takes account of demand uncertainty and multiple cost factors, such as transportation cost, time cost, waiting cost before consolidation, penalty cost of not full load after distribution, track changing cost, and customs clearance fee. A complicated mixed-integer programming (MIP) model is presented to describe the problem. Then a solution method based on binary particle swarm optimization (BPSO) is designed to solve the model of different scales of cases. Extensive numerical experiments generated from real-world data are conducted to validate the effectiveness of the proposed model. Moreover, we compare the efficiency of the solution method with a commercial solver and a heuristic algorithm based on variable neighborhood search (VNS). Results show that our solution method can optimally solve the problem in small-scale cases and get near-optimal solutions for large-scale problem instances. The proposed mathematical model and the calculation results may provide valuable insights for both business owners and government.