Optimizing Crop Planting Strategy Based on Goal Programming and Differential Genetic Algorithm

Abstract

The formulation of crop planting strategy is of great significance to effectively utilize rural cultivated land resources and promote the sustainable development of rural economy. The optimal planting strategy is to make full use of cultivated land resources to plant crops in order to obtain the maximum expected profit under the premise of following the law of crop growth. Based on the given rural planting conditions, the growth law of various crops, the expected sales volume of various crops, the yield per mu, the planting cost and the uncertainty of the selling price, this paper constructs a single objective programming model to maximize the expected total profit of crops as the objective function, and introduces conditional value at risk to carry out robust optimization of the objective function. The uncertainty parameters were simulated by Monte Carlo method, and their expectation and variance were estimated by kernel density estimation method. Finally, differential genetic algorithm was used to solve the model, and the optimal planting strategy was obtained.