Research on agricultural planting optimization model based on Harris Hawk Optimization algorithm

The application of computer optimization algorithms in agricultural planting has become increasingly widespread. This study, based on rural background data, constructs an agricultural planting optimization model to assist farmers in optimizing planting decisions, thereby increasing profits and reducing risks. A single-objective optimization model was initially employed, solved using the Harris Hawk Optimization (HHO) algorithm and the Genetic Algorithm (GA) for comparison. HHO demonstrated superior performance in terms of convergence speed, solution accuracy, and stability, achieving a maximum profit of 2.27 billion yuan. The model was then extended to multi-objective optimization, where an improved Multi-Objective HHO (MOHHO) was combined with Monte Carlo simulation to account for market volatility, ultimately achieving a maximum profit of 2.87 billion yuan. The results indicate that this model effectively balances profit and risk.