Robust service network design problem under uncertain demand

This study examines a robust service network design problem, which aims to select transportation services and distribute commodity flow for consolidation carriers. A robust optimization approach with a penalty limit constraint is proposed to formulate the problem. Furthermore, to make a balance between objective value and penalty violation, we introduce the concept of robustness index. A decomposition method with valid cuts is proposed to solve the problem. Numerical results show that the efficiency of the proposed algorithm. A real data set released by a logistics company in east China is imported to validate the robust optimization approach, which yields a robust parcel delivery network design with satisfying out-of-sample performances.

Automated summary

This study proposed an optimization method for a robust service network design problem, balancing objective value and penalty violation with penalty limit constraint and robustness index. A decomposition method was introduced to solve the problem, with numerical results demonstrating the efficiency of the algorithm. The robust optimization approach was validated using real data, resulting in a robust parcel delivery network design with satisfactory out-of-sample performances.