Abstract
Integrated transportation systems providing multiple types of services are attracting increasing attention due to the diversification of demands. In this paper, we propose both deterministic and two-stage robust optimization formulations for the service network design problem considering multiple types of services. A probability-free uncertainty set is employed to deal with demand uncertainty in the proposed robust model. We implement a column-and-constraint generation approach to solve the robust model, which outperforms the Benders decomposition method. Comparative results indicate that it helps reduce the total cost and the number of vehicles to consider multiple service types in the network.
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