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In order to solve the weapon-target assignment (WTA) problem rapidly, several key operations in genetic algorithm are improved. A unique fire unit sorting-based population initialization method is addressed. With the niche share function and adaptive thinking, an improved niche-based adaptive genetic algorithm (NAGA) is designed and achieved. In the end, the simulation for real time and reliability is examined. The result illustrates that this algorithm is valid with better performance and convergence rate.