Analysis of different approaches to cross-dock truck scheduling with truck arrival time uncertainty

This paper studies scheduling of inbound trucks at the inbound doors of a cross-dock facility under truck arrival time uncertainty. Arrival time of an inbound truck is considered to be unknown. In particular, the cross-dock operator only acknowledges the arrival time window of each truck, i.e., the lower and upper bounds of any inbound truck's arrival time. In absence of any additional information, the cross-dock operator may use three approaches to determine a scheduling strategy: deterministic approach (which assumes expected truck arrival times are equal to their mid-arrival time windows), pessimistic approach (which assumes the worst truck arrivals will be realized), and optimistic approach (which assumes the best truck arrivals will be realized). In this paper, a bi-level optimization problem is formulated for pessimistic and optimistic approaches. We discuss a Genetic Algorithm (GA) to solve the truck-to-door assignments for given truck arrival times, which solves the deterministic approach. Then the GA is modified to solve the bi-level formulations of the pessimistic and the optimistic approaches. Our numerical studies show that an hybrid approach regarding the pessimistic and the optimistic approaches may outperform all of the three approaches in certain cases. Published by Elsevier Ltd.