Crop Planting Optimization Decision-Making Based on Goal
DOI:
https://doi.org/10.54097/ehrcrw41Keywords:
Multidimensional Linear Programming, Multivariate Mixed Integer Programming, Monte Carlo Algorithm, Spearman's Rank Correlation Coefficient Model.Abstract
To scientifically plan the high-standard farmland construction plan, fully promote the implementation of the high-standard farmland construction task and formulate a scientific and reasonable planting strategy for a village in a mountainous area of North China. This article comprehensively consider the expected sales volume, yield per mu, planting cost and selling price, and planting risk, and combined with the allocation of land resources and the crop planting situation of six villages to obtain the optimal planting plan for rural crops from 2024 to 2030. At the same time, we obtain the substitutability and complementarity between crops according to the planting conditions of crops and adjust the planting strategy. This article also introduced climate risk factors to assess the impact of climate on crop cultivation in northern China. The solution proposed in this article is not only better applicable to the polymorphic planting planning in North China based on predecessors but also innovatively introduces a planting plan that is selected according to crop relevance. This program can not only reduce the range of crop types and the pressure on field management; It also helps create rural specialties, turn crops into rural characteristic resources, and realize product advantages. This has a positive reference for constructing rural areas with Chinese characteristics.
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