Multi-objective Optimization Genetic Algorithm for Multimodal Transportation

The multimodal transportation is an effective manner in reducing the transportation time and cost. However, the programming of multimodal transportation is very complex and belongs to NP difficulty problems. Therefore, an optimal model based on the graph structure was firstly formulated for the multimodal transportation with two optimal objectives including the transportation time and the transportation cost. An optimized algorithm with two layers was then proposed after characterizing the formulated model. The upper level was applied to find the global optimal Pareto fronts and the transportation path, whereas the lower level was to find the optimal path and the transportation manner. At last, a numerical simulation was performed to validate the model and the proposed algorithm. The results show that the proposed algorithm can find a series of Pareto front solutions, which indicates that the formulated model and proposed algorithm are effective and feasible.