Border patrol route and strategies optimization based on Genetic Algorithm and game theory

Since the terrorist attacks of September 11, 2001, terrorist attacks, weapons, drug-related crime and illegal immigration have had a more frequent occurrence, which has mainly been concentrated in border region. Therefore, prevention and protection are the most fundamental conditions to prevent cross border terrorist incidents from occurring. Accordingly, designing a high efficiency patrol route for the U.S. Customs and Border Protection agency is much more vital and meaningful. So, the Genetic Algorithm(GA) mainly focus on the optimization of patrolling path model that is calculated by taking into account the capture rate and patrolling network cost. On the other side, Stackelberg model is introduced to make the patrol route intelligent, which help defender change the strategy and find the best route effectively whenever the attacker change the escape route. Meanwhile, in the case study, the author chooses 10 cities along the Texas-Mexico border as research objects to verify the optimization method. Key words: Genetic algorithm, Game theory, border security, patrol routing, GI