Cross-docking is a logistic strategy that facilitates rapid movement of consolidated products between suppliers and retailers within a supply chain. It is also a warehousing strategy that aims at reducing or eliminating storage and order picking, two of which are known to be major costly operations of any typical warehouse. This strategy has been used in the retailing, manufacturing, and automotive industries. In a cross-dock, goods are unloaded from incoming trucks, consolidated according to their destinations, and then, loaded into outgoing trucks with little or no storage in between.
In this thesis, we address an integrated cross-dock door assignment and truck scheduling problem in which the assignment and sequencing of incoming trucks to strip doors and outgoing trucks to stack doors is optimized to minimize the total time to process all trucks. We present a mixed integer programming formulation to model this problem and some valid inequalities to strengthen the formulation. We also present two metaheuristics to obtain high quality solutions in reasonable CPU times. These algorithms use a mix of composite dispatching rules, constructive heuristics, local search heuristics which are embedded into a greedy randomized adaptive search procedure (GRASP) and an iterated local search (ILS). Results of computational experiments are presented to assess the performance of the proposed algorithms, in comparison with a general purpose solver
