Ricerc@Sapienza

This paper addresses progressive network recovery under uncertain knowledge of damages. We formulate the problem as a mixed integer linear programming (MILP), and show that it is NP-Hard. We propose an iterative stochastic recovery algorithm (ISR) to recover the network in a progressive manner to satisfy the critical services. At each optimization step, we make a decision to repair a part of the network and gather more information iteratively, until critical services are completely restored.

After a massive scale failure, the assessment of damages to communication networks requires local interventions and remote monitoring. While previous works on network recovery require complete knowledge of damage extent, we address the problem of damage assessment and critical service restoration in a joint manner. We propose a polynomial algorithm called Centrality based Damage Assessment and Recovery (CeDAR) which performs a joint activity of failure monitoring and restoration of network components.

This article examines a practical experiment that was carried out on 6 May 2016 at the University of Udine, in Pordenone, in order to honor the victims of the 1976 earthquake that struck Friuli. The experiment involved a test evacuation of the University's campus. The test group was composed of 53 students who, before the evacuation drill, had attended a lecture on disaster prevention and emergency management. The control group was a class of 13 students who had been provided with no preventative information. This study made use of two methodologies: 1.