An agent-based modeling and evolutionary optimization approach for vulnerability analysis of critical infrastructure networks

Abstract

Critical infrastructure networks include the highly complex and interconnected systems that are so vital to a city or state that any sudden disruption can result in debilitating impacts on human life, the economy and the society as a whole. Some of the interdependencies among infrastructure components are perhaps unforeseen and methods for vulnerability analysis of infrastructure networks should therefore incorporate the possibility of potential unforeseen interdependencies in such networks. This paper proposes using an optimization approach to iteratively search for potential unforeseen interdependencies and failures that can maximize connectivity loss in infrastructure networks due to cascading failures. In order to illustrate the proposed approach, an agent based model of an infrastructure network and its known interdependencies has been presented, with a genetic algorithm applied to search for potential unforeseen interdependencies as well as node failures that can result in the maximum loss of infrastructure network connectivity. © Springer-Verlag Berlin Heidelberg 2013.