We study a new service network design problem for an urban same-day delivery system in which the number of vehicles that can simultaneously load or unload at a hub is limited. Due to the presence of both time constraints for the commodities and capacity constraints at the hubs, it is no longer guaranteed that a feasible solution exists. The problem can be modeled on a time-expanded network and formulated as an integer program. To be able to solve real-world instances, we design and implement three heuristics: (1) an integer programming based heuristic, (2) a metaheuristic, and (3) a hybrid matheuristic. An extensive computational study using real-world instances (with different geographies, market sizes, and service offerings) from one of China's leading comprehensive express logistics service providers demonstrates the efficacy of the three heuristics.
H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, March 2020
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