Optimization of Crop Planting Strategies Based on Multi-Objective Linear Programming

Abstract

Nowadays, rural farmland is facing the problems of how to plant a wide variety of crops according to local conditions, how to maximize economic benefits, and how to promote sustainable development of the environment. This article is based on the research of crop planting, production, and sales data in a rural area in 2023. Multiple multi-objective linear programming models are established to solve the optimal planting plan for the rural area from 2024 to 2030 under different conditions. Firstly, data preprocessing is carried out to obtain expected sales volume and sales unit price. Observing the data, it is found that the planting of grain crops and vegetable crops are independent. Therefore, two multi-objective linear programming models are established separately. Their objective functions are to maximize crop sales revenue and minimize crop planting costs. The two model constraints mainly include: bean planting frequency constraint, planting area constraint, planting range constraint, planting situation and yield relationship constraint, etc. For vegetable crops, there is a two season planting crop constraint. Four multi-objective linear programming models are used to solve the planting plans for grain crops and vegetable crops in two scenarios: when the actual production exceeds the expected sales volume and when the excess is unsold, and when the excess is sold at a 50% discount to the 2023 sales price.