A maximal multiple coverage and network restoration problem for disaster recovery. (2020)

• Record Type: Journal Article
• Authors: Iloglu, Suzan; Albert, Laura A.
• Is Part Of: Operations research perspectives. Volume 7(2020)
• Publication Date: 2020
• Subjects: OR in disaster relief -- Maximal multiple coverage problem -- Network restoration -- Scheduling on parallel servers -- Emergency response; Operations research -- Periodicals; Management science -- Periodicals; 658.403405
• DOI: 10.1016/j.orp.2019.100132
• Languages: English
• ISSNs: 2214-7160

Abstract

Highlights: We model how to respond to emergency demand with backup coverage after disasters. We study how to restore network components after a disaster to aid emergency response. We consider the movement of emergency responders on a network over a time horizon. Our model informs decisions regarding how to restore interdependent infrastructure. Abstract: The recovery of physically damaged infrastructure after disasters is critical to efficiently deliver disaster relief supplies and emergency services. The physical damage to road infrastructure from disasters can result in decreased road link capacities and an inability to meet the community's emergency demand. This paper provides an infrastructure restoration plan for delivering critical services after disasters. We present a maximal multiple coverage and network recovery problem for the recovery and restoration of infrastructure systems after disasters. In the model, recovery crews make damaged arcs available by repairing components over a time horizon in a disrupted network. The model relocates emergency responders using the available arcs in the network to maximize multiple coverage of emergency service demand over the time horizon. We present two heuristics for the model. The first uses the Lagrangian and the linear programming relaxation solutions of the problem, and the second uses an integer rounding procedure applied to the linear programming relaxation solution. We test the model using a real-world example representing the road infrastructure and emergency services of the Bronx Borough in New York, NY during Hurricane Sandy. The results demonstrate that the integer rounding heuristic is effective in identifying near-optimal solutions. Our computational study suggests that our model can aid emergency managers in achieving their goals by scheduling effective restoration activities for real-time disaster recovery and long-term recovery planning.