Trajectory Optimization of Tobacco Seedling Planting Mechanism Based On NSGA-II Algorithm and Response Surface
DOI:
https://doi.org/10.23055/ijietap.2026.33.4.11377Abstract
In order to ensure the uprightness of tobacco seedlings during transplanting and improve the transplanting quality, this paper proposes a hybrid optimization framework that integrates the NSGA-II multi-objective genetic algorithm and response surface methodology (RSM). Taking the planting depth and lateral offset as the optimization objectives, nine key mechanism parameters affecting the planting trajectory are selected as the initial design variables. Firstly, with the global search capability of the NSGA-II algorithm, we locate the feasible region that fits the constraints of the mechanism and obtain the optimal solution set. Then we screen out five significant influencing factors based on the Plackett-Burman test, and use the Box-Behnken response surface design to carry out the localized refinement modeling. Based on the regression model, an optimal combination of parameters is obtained; the mechanical trajectory under this set of parameters meets the agronomic requirements for transplanting.
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