Determining the most vulnerable components in transportation networks

Abstract

Transportation network, electricity distribution network, supply chain network, telecommunication network are the main critical infrastructure networks used to pro vide products and services to customers. Man-made intentional attacks may cause serious problems in these critical infrastructure networks, especially in large cities. For example, terrorist activities are man-made intentional attacks. As a result of terrorist attacks, a metro station may become unusable for transportation, an airport may be unable to provide service, a bridge may be closed to vehicle traffic, and the communi cation may be prevented due to the damaged telephone lines. When such attacks are carried out by an intelligent agent, disruptions may be even bigger. In this study, it is aimed to determine the components that are affected most by disruptions in a transportation network. These most affected components are the most vulnerable components in the network. Therefore, a two-level mathematical model has been established that can periodically identify the most vulnerable components. In the developed model, the virtual attacker is the leader who wants to cause the most dis ruption in the transportation network (minimizing the amount of flow on the network), and the system operator is the follower who wants to operate the transportation net work optimally after the disruption (to maximize the amount of flow on the network). The components that can be attacked in the model are stations and it is considered that a station is completely shut down after an interdiction. A tabu search heuristic is used as the solution method of the proposed model. The developed tabu search method has been tested on randomly generated different sized networks and its performance is assessed in comparison with a complete enumeration and a greedy approach.