Research on the location problem of unmanned border and coastal air defense anti-aircraft gun

In the proposed work, an improved genetic algorithm(IGA) has been devised to solve the model of location problem of unmanned border and coastal air defense anti-aircraft gun. The crossover and mutation probabilities can be adjusted adaptively, by introducing fuzzy operators into the crossover and mutation links, according to the standard deviation of population fitness, so as to achieve the goal of fast convergence and the improvement of robustness of the algorithm. The experimental results show that IGA proposed in this work provides promising results in solving the location problem of unmanned border and coastal air defense anti-aircraft gun.