Cross-dock job assignment problem in space-constrained industrial logistics distribution hubs with a single docking zone

This paper addresses a cross-dock operations problem in space-constrained industrial logistics distribution hubs. In these hubs, the number of incoming trucks exceeds the number of docks available, and inbound trucks and orders arrive at random. The solution lies in minimising the waiting time of trucks by coordinating the pick up/delivery sequences of inbound and outbound orders in the storage zones. A mathematical model and a meta-heuristics algorithm, which is based on a genetic algorithm, are developed to address the problem. This research is innovative because the proposed algorithm allows the insertion of inbound orders that arrive at random into the schedule, without causing any significant disturbance to the original outbound order schedule. Computational experiments are conducted to examine the performance of the algorithm under heavy and normal cross-dock conditions. Results show that the algorithm reduces the total makespan of storage operations by 10% to 20% under heavy and normal conditions. The research study benefits manufacturers by increasing cross-docking efficiency in industrial logistics systems characterised by limited temporary storage capacity and the random arrival of inbound trucks.