Optimum Route and Transport Mode Selection of Multimodal Transport with Time Window under Uncertain Conditions

Aiming at the problem of multimodal transport path planning under uncertain environments, this paper establishes a multi-objective fuzzy nonlinear programming model considering mixed-time window constraints by taking cost, time, and carbon emission as optimization objectives. To solve model, is de-fuzzified expectation value method chance-constrained method. Combining game theory with weighted sum method, cooperative theory-based proposed. Finally, effectiveness algorithm verified in real intermodal network. The experimental results show that proposed can effectively improve performance obtain optimal satisfies time requirement, are better than MOPSO NSGA-II, reducing transportation costs emissions. Meanwhile, influence uncertainty factors on route analyzed. will significantly increase cost emissions affect choice mode. Considering reliability provide more robust effective solution for transportation.