Solution approaches for facility location of medical supplies for large-scale emergencies
Computers and Industrial Engineering
A bilevel mixed-integer program for critical infrastructure protection planning
Computers and Operations Research
A bi-objective approach for shortest-path network interdiction
Computers and Industrial Engineering
Evolutionary multi-objective optimization: a historical view of the field
IEEE Computational Intelligence Magazine
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Super facilities versus chaining in mitigating disruptions impacts
Computers and Industrial Engineering
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The disruption of critical infrastructures is currently a major security concern. Preparedness in the context of critical infrastructures can be understood as a state of readiness that translates to the development of a plan to support, maintain or restore infrastructure services in cases of critical disruption. From the perspective of this manuscript, infrastructure preparedness plans are then strongly related to the types of disruptions within the infrastructure. This paper presents an attacker and defender contest in the context of service network as a first step to address the adequate protection of infrastructures against external failure causing events and to integrate the research areas of: vulnerability analysis and protection strategy development. The paper introduces a robust protection analysis approach that ties together vulnerability analysis with protection strategy development with purpose of providing infrastructure protection strategies to reduce points of vulnerability. The contest considered generates two multi-objective models that are solved via an evolutionary algorithm. The solutions to each of these problems allow the defender to identify key network elements that allow the attacker to affect the most damage in a network service and then, based on this information, developing a set of cost effective robust protection strategies. The techniques and approaches developed are illustrated in an electric power system context.