Research on Optimal Crop Planting Strategy Based on Mixed-Integer Programming
Changcai Guo, Jiachen Zhang, Yi Lan · Academic Journal of Science and Technology · 2024
This study aims to explore the optimal crop planting strategy from 2024 to 2030 based on the Mixed-Integer Programming (MIP) method. Through systematic organization and in-depth analysis of rural crop cultivation and related statistical data collected in 2023, it was found that different types of crop planting plots have no significant impact on sales prices but do affect planting costs and yield per acre. The study also considered the impact of irrigated and greenhouse planting areas, as well as planting seasons on sales, costs, and yield. By establishing a crop planting profit maximization model and introducing 0-1 variables to record the planting strategy for the next 7 years, we used MATLAB software and the CPLEX solver to solve this single-objective mixed integer programming model. The analysis of the model results indicates that crops exceeding the expected sales volume should be discounted in the current quarter in a timely manner to maximize overall revenue.