摘要：AbstractIn this paper, the continuous transportation network design problem with demand and cost uncertainties is studied while the generated trip between each origin-destination pair is deterministic. Propose a bi-level uncertain model with robust optimizations. In the upper-level problem, the costs of expansion are uncertain by adding random variables to the cost function coefficients. Every random variable belongs to [0,1]. In the lower-level problem, the demand between each origin-destination pair is uncertain and belongs to a bounded interval and an ellipsoid. Then apply a genetic algorithm combined with the Frank-Wolfe algorithm to solve the model. Numerical examples suggest that the robust model with uncertain data has the advantage of operability and stability over the deterministic model.
