Research on Crop Planting Strategies Based on Optimization Algorithms

Abstract

With the development of organic planting industry, choosing suitable crops and optimizing planting strategies are of great significance to the sustainable development of rural economy. In order to help a village design the optimal planting plan for crops in 2024∼2030, this paper first builds an objective function based on the treatment of expected sales exceeding the situation in multiple scenarios, sets constraints according to the requirements, models and solves to obtain the optimal planting strategy[1], and comprehensively examines the model's stability and and reasonableness based on the sensitivity analysis. Secondly, Monte Carlo algorithm is introduced to search for the optimal planting strategy of many simulated scenarios, and particle swarm algorithm is used to analyze the uncertainty and planting risk of global optimization of planting strategy. Pearson's correlation coefficient is then used to introduce linear regression model and nonlinear regression model to analyze the substitutability and complementarity between crops, and the best planting plan is obtained through comparison.