Optimization method for ground-based air defense deployment based on multi-population genetic algorithm

Cooperative air defense deployment is a critical research area in land-based air defense command and control. To address air defense issues in a sector-shaped area, this study discretizes the deployment space and optimizes firepower coverage to achieve uniform distribution of fire units in depth. Fire unit dispersion is introduced to constrain deployment results, establishing an optimization model for cooperative air defense in sector-shaped areas. A multi-population genetic algorithm is employed for optimization, enhancing evolutionary speed and preventing premature convergence observed in single-population evolution. The algorithm and optimization model are validated through specific deployment cases.