Research on the allocation of kiwifruit yield tasks in planting areas based on improved local search algorithm

In the process of assigning kiwifruit production tasks, due to the large planting area of kiwifruit, it takes a long time to allocate suitable planting intervals for kiwifruit trees, resulting in an increase in algorithm execution time and cost. Therefore, it is proposed to further improve the local search algorithm based on the improved local search algorithm for kiwifruit yield task allocation, combined with the global search ability of the sparrow search algorithm and the introduction of variable helix factors and dimension wise lens learning strategies. The simulation results show that the improved local search algorithm has a faster convergence speed, and the curve has converged after 500 iterations. When the kiwifruit yield task is less than 30 tons, H is set to 2, and when the kiwifruit yield task is greater than 40 tons, H is set to 4. When the yield task is less than or equal to 40 tons, planting area 3 can meet the optimal planting interval. When the yield is greater than or equal to 50 tons, planting area 4 meets the requirements. Therefore, using an improved local search algorithm to allocate intervals between kiwifruit trees has good allocation performance, and can allocate kiwifruit trees reasonably based on different yield tasks and planting area.