In view of site selection problems for support and logistics notes of ground-based air defense equipment under complex constrains caused by modern ground-based air defense operations increasingly turning towards distributed structures, modular design, and enhanced mobility, this paper tackles a complex problem of selecting optimal sites for support and logistics nodes, and proposes an innovative genetic-K-means-genetic algorithm (GAKGA). And the algorithm is utilized for stratifying different combat modules into different hierarchical tiers by hierarchical clustering idea, reflecting the intricacies of real-world operational constraints. Within each tier, the K-means algorithm is utilized to identify solutions satisfied with the problem’s constraints. By integrating genetic algorithms, the initialization of the K-means algorithm is optimized, leveraging the genetic algorithm’s strength in global search optimization. The final step involves using genetic algorithms to refine the selection of support nodes based on the results from each tier. The experimental results show that the enhanced GAKGA significantly improves solution efficiency, yielding shorter paths in complex site selection problems, thus facilitating a more agile response to the support needs of distributed ground-based air defense equipment.