A scenario-based simultaneous game approach for risk-averse facility protection problem

Abstract In this research, protecting facilities from intentional attacks under operational and disruption risks is modeled as a discrete scenario-based simultaneous game between a defender and an attacker, in which the information of their resource allocation is kept secret. In the presence of stochastic disruptions, a risk measure is incorporated into the defender. To deal with the proposed scenario-based simultaneous game in which the defender and the attacker have different objective functions, we develop an adaptive algorithm based on a maximum-likelihood sampling method to identify its mixed-strategy Nash equilibrium solution with respect to the conditional value-at-risk. In the experimental part, through comparative experiments, it is shown that the model of this article improves the decision-making benefit of the defender.