Route Optimization of Travelers' Intermodal Transport Considering Bounded Rationality

To enable travelers to reach their destination in a relatively short time while reducing travel costs, this paper establishes a multi-objective path optimization model by analyzing the impact of factors such as weather reduction coefficient and road congestion coefficient on travelers' route selection. And combine quantum genetic algorithm with an elite strategy to solve multi-objective models. Finally, the rationality of the model and algorithm is verified by a case. The results show that in the travelers' intermodal transport network considering bounded rationality, the choice of travel route will change with the change of road traffic congestion and weather conditions, and travelers need to make decisions according to the specific requirements of the day of departure. Using bounded rationality to describe travelers' expectations can reflect their travel needs well.