Hub-and-spoke network design under congestion: A learning based metaheuristic: .

This paper models a single allocation multi-commodity hub-and-spoke network problem through a bi-objective mathematical model, considering the congestion in both hubs and connectionlinks. A novel aggregation model is developed based on a general GI/G/c queuing system toevaluate the congestion of the flow of the multiple products in the hubs. The proposed model isthen solved using a novel learning-based metaheuristic based on NSGA-II, k-Means clusteringmethod, and an Iterated Local Search (ILS) algorithm. The proposed model and solution algorithm are validated through a set of experiments against optimal solutions, and benchmarked against four existing well-known algorithms.