Optimal protection of complex networks exposed to a terrorist hazard: A multi-objective evolutionary approach

Abstract

The present paper proposes an approach for prioritizing the protection of a network system exposed to a terrorist attack. The approach is based on a multi-objective optimization (MO) formulation for finding Pareto optimal solutions with respect to two indicators measuring the damage that the attack may cause: the time to reach all network destination nodes (TTRAD) and the average number of persons affected (ANPA). The MO is tackled by means of a multi-objective evolutionary algorithm (MOEA) that combines the basic concepts of dominance with the general characteristics of evolutionary algorithms. Within this optimization scheme, the goodness of each alternative protection scheme is quantified by a combination of cellular automata (CA) and Monte Carlo (MC) simulation. Numerical examples illustrate how the approach is capable of identifying effective protection schemes.