An optimization model for multimodal transportation decisions based on congestion information

Focusing on the reality of growing traffic congestion and the external uneconomic of congestion, the influences of congestion time and congestion opportunity cost on multimodal transport modes selection are proposed. A virtual multimodal transportation network with congestion information is designed, and the optimization model of the multimodal transportation decision is established to minimize transportation costs and congestion time. Hence, an optimal solution using the self-adapting inertia weight particle swarm algorithm is proposed in this paper. The simulation results and analysis prove the effectiveness of the proposed solution.