Research on Agricultural Products Planting Strategies Based on Integer Programming and Stochastic Programming

Abstract

In this paper, by applying the algorithms of integer programming and stochastic programming, we have studied in depth the crop planting strategy of a rural area in North China. First, we constructed an optimization model based on integer planning and stochastic planning agricultural planting strategies by exhaustively analyzing the detailed data of cultivated land and crops in the area. Further, we introduced stochastic variables to simulate the market uncertainty and the risk in the planting process, so as to propose an optimal planting scheme based on robust optimization theory. In addition, Spearman's correlation coefficient and ordinary least squares (OLS) regression analysis were used in this paper to further optimize the planting strategy by taking into account the substitutability and complementarity among crops. Through the continuous iteration and refinement of these methods, this paper significantly improves the accuracy and practicability of the planting decision model, and provides a valuable reference strategy for scientific planting of crops.