An improved simulated annealing-linear programming hybrid algorithm applied to the optimal planting plan of crops

The cropping planning includes the selection of cropping plot and cropping amount every season, which is of great significance for making full use of land resources and realizing sustainable development of rural economy. Simulated annealing algorithm is a stochastic optimization method based on probability. However, the traditional algorithm is not good in solving the large-scale problem with high variable dimension, and it takes a lot of computation cost to find the optimal solution. Firstly. Based on the traditional simulated annealing algorithm, this paper introduces the marginal contribution of crops to select the most suitable crops for different cultivated land types and reduce the number of model decision variables. Furthermore. In this paper, the optimal strategy for maximizing the profit of crop planting is given by considering the factors such as diversification, centralization, complementarity, market fluctuation and climate change.