Mathematical Optimization Analysis of Simulated Annealing Algorithm Based on Differential Evolution and Robust Optimization in Organic Crop Cultivation

For the development of rural organic farming, this paper analyses the raw data and constructs a mathematical model to maximize crop yields and increase farmers' incomes. Two single-objective planning models were constructed to increase crop yields in 2023: considering unsold crop surpluses and selling surpluses at a discounted price (50% of the selling price). The model was solved using 14 constraints and a differential evolutionary algorithm to obtain an optimized planting plan for 2024-2030. Due to the uncertainty of the variables, a robust optimization model was developed to ensure maximum profitability of cultivation under extreme conditions. In addition, an efficient solution method is proposed to obtain the optimal planting plan for different crops. The results show that introducing such constraints leads to a significant increase in overall profits. This paper is an analysis of the strengths and weaknesses of the model and an exploration of its potential for long-term strategic planning, to provide a reference for promoting sustainable rural development.