Optimization Research of Crop Planting based on Dynamic Planning Model and Optimal Planting Strategy

Abstract

This paper focuses on the problem of how to choose suitable crops and optimize planting strategies to improve production benefits and reduce planting risks. A dynamic planning model is constructed through data analysis, and based on the crop planting data in 2023, taking into account the characteristics of different types of arable land and the growth pattern of crops, two optimal planting strategies are proposed under two sales scenarios: firstly, the waste generated when the crops exceeding the sales expectation are unsaleable; and secondly, the excess portion will be sold at a reduced price of 50%. The objective function is constructed through the greedy algorithm and the dynamic programming model is solved to obtain the optimal planting area allocation scheme for the next seven years. Uncertainties in crop sales volume, mu yield, planting cost and sales price were further considered, and Monte Carlo simulation was used to generate stochastic scenarios. For different market conditions and climate changes, the simulation results demonstrate the possible crop returns and risk scenarios in the next seven years. Through a large number of simulations, this paper counts the acreage and yield expectations of various crops, and combines the data to optimize the dynamic planning model and analyze the uncertainties such as planting risks, which helps villages to develop more adaptive planting scenarios under complex external conditions. The Spearman correlation coefficient is used to conduct correlation analysis, and the complementarity matrix is constructed by combining the substitutability and complementarity of crops. Through the substitutability analysis, it is concluded that there is a competitive relationship between crops in the utilization of resources, which needs to be accurately weighed in order to optimize the allocation of resources; through the complementarity analysis, it is concluded that a reasonable combination of different crops can improve the overall efficiency. By constructing the decision model and incentive mechanism, the effects of substitutability and complementarity on planting strategies are effectively reflected. The results show that the optimization scheme not only improves the production efficiency of the villages, but also has high robustness and replicability, and can provide useful reference for crop planting planning in similar areas.