A Bi-Level Programming Model for Hierarchical Maximal Covering Hub Location Problem under Disruption in Hubs

The hub location problem is one of the most fundamental and crucial issues in transportation systems and decision-making. The primary purpose of a transportation network is to transfer traffic between demand points via a hub, and hubs are essential to this process. The failure of hubs has garnered considerable attention of researchers in recent years. This research examines the problem of hierarchical hub location using bi-level programming. This study presents a model for optimal hub coverage. In non-central hubs, disruptions are intentional. The objective function of the second level is to minimize the problem's coverage by disabling the hubs, whereas the objective function of the first level is to minimize the problem's damage while expanding its coverage. The studied problem was solved using the simulated annealing and the full enumeration method. The proposed model has been solved for a variety of different scenarios, including fluctuating demand and hub count, fluctuating discount factors between hubs, and fluctuating coverage radii. According to the numerical results, as the covering radius increases, the number of located nodes and the problem's coverage also increase. In conclusion, an analysis of the employed solution methods concludes that the proposed meta-heuristic method is both effective and applicable to larger data sets.