Scientific Development Research

This paper takes a mountainous village in North China as the research object. Focusing on the optimization of its crop planting strategy, the mixed integer linear programming (MILP) model is adopted to optimize the crop planting plan from 2024 to 2030, aiming to enhance production efficiency and reduce the risks brought by market fluctuations and uncertainties, providing support for the sustainable development of the village. For multi-stage constrained optimization problems, the model comprehensively considers multiple factors such as plot type, crop rotation, continuous cropping taboos, seasonal restrictions, and market demand, and respectively explores two scenarios of overstocking and price reduction when the output exceeds the demand. Establish a mixed-integer linear programming model to maximize the total revenue and control the planting area and crop rotation requirements. The results show that in the case of overstocking, waste can be avoided by precisely controlling the planting area of crops, while in the case of price reduction, moderate overproduction is allowed and the gains from overproduction and the losses from price reduction can be balanced.

Mixed Integer Linear Programming (MILP) ;Multi-objective optimization; Planting strategy; Risk management