An adaptive large neighborhood search heuristic for solving the reliable multiple allocation hub location problem under hub disruptions

The hub location problem (HLP) is one of the strategic planning problems encountered in
different contexts such as supply chain management, passenger and cargo transportation
industries, and telecommunications. In this paper, we consider a reliable uncapacitated multiple
allocation hub location problem under hub disruptions. It is assumed that every open hub facility
can fail during its use and in such a case, the customers originally assigned to that hub, are either
reassigned to other operational hubs or they do not receive service in which case a penalty must
be paid. The problem is modeled as two-stage stochastic program and a metaheuristic algorithm
based on the adaptive large neighborhood search (ALNS) is proposed. Extensive computational
experiments based on the CAB and TR data sets are conducted. Results show the high efficiency
of the proposed solution method.