LAUSR

To develop low-carbon transport and promote sustainable economic development, this paper took the uncertainty in highway transport speed and transshipment time into account in the actual transport process and established multi-objective path-decision models of multimodal transport under different carbon policies. The expectation values of nonlinear uncertainties were estimated by Law of Large Numbers (LLN), and the models were solved by the K-shortest paths algorithm and non-dominated sorting algorithm (NSGA-II), whose advancement and effectiveness were verified through the comparison of SPEA2. Based on the Pareto theory, the optimally symmetrical compromise between the objectives and the influence of the transport speed uncertainty and carbon emission policies on path decisions were quantified and discussed. Taking the multimodal transport network of West Africa as the experimental background, the practicability of the path-decision results is analyzed, and a trade-off analysis is also conducted to provide the theoretical foundation for future freight transport planning.