Defense of High-Speed Rail With an Evolutionary Algorithm Guided by Game Theory

High-speed rail (HSR) holds promise as an investment to modernize the transportation infrastructure of the United States of America and support its national economy. The half trillion dollar price tag necessitates thorough analysis and planning to ensure long-term success, including a well formulated vulnerability analysis to identify an optimal or near-optimal strategy for deploying protective technologies and infrastructure that will render the HSR network resilient to disruptions induced by natural disasters and terrorist threats. This paper embeds a game-theoretic vulnerability assessment technique that considers the impact of defending network links into a genetic algorithm, which searches for a near-optimal assignment of finite defensive resources to the links of the network. The terms link and edge are used interchangeably in this paper. The approach is applied to the incremental HSR network deployment map given by the U.S. High-Speed Rail Association, describing network construction over a 15-year period from 2015 to 2030. Our results suggest that, over the life of the HSR network, a strategy utilizing relocatable defenses could achieve significant savings compared to less flexible strategies that rely solely on static defenses.