Aiming at the problem of low efficiency of path planning from plug seedling transplanting to low density plug, this paper proposes ant colony-genetic and genetic-ant colony interaction algorithms based on genetic algorithm and ant colony algorithm to optimize the sparse planting transplanting path. Through simulation experiments, the fixed sequence method and other five algorithms were used to calculate the transplanting path length from 72-32,72-50,128-50,128-32 hole trays. The performance of the algorithm in optimizing path length and computing time is compared and analyzed, and the stability of the algorithm is evaluated by relative standard deviation. The experimental results showed that the average path length of the genetic-ant colony algorithm was 59.3 % shorter than that of the fixed sequence method in the 72-hole to 32-hole plug transplanting. The average calculation time was 5.15 S, and the relative standard deviation median was about 1.5 %. The average path length of the genetic-ant colony algorithm is shortened by 19.2 %, the average calculation time is 13.50 s, and the median relative standard deviation is about 1 %. The research shows that the two interactive algorithms have improved the performance of the original algorithm. The comprehensive performance of the genetic-ant colony algorithm is better than that of the ant colony-genetic algorithm. It shows superior optimization and high stability in the case of different number of seedlings, and shows convergence in the iterative process. The behavior has efficient global search ability, which can meet the work requirements of the optimal path of thin planting transplanting of greenhouse plug seedlings, and provides a strong reference for selecting algorithms in complex path planning problems.