Two-stage conflict robust optimization models for cross-dock truck scheduling problem under uncertainty

This paper studies the cross-dock truck scheduling problem, which considers the uncertainty of trucks' arrival and operational times. We introduce a concept named conflict and present a two-stage optimization model, aiming at minimizing the total cost and number of conflicts. Furthermore, an extended model by introducing K-means clustering is presented, for which the performance guarantees are provided to validate its efficiency. A column and constraint generation algorithm, which is proved to converge in a finite number of iterations, is designed to solve the developed models. Extensive numerical experiments are conducted to validate the performance of the developed models and algorithm.