Year: 2025
Type: article
Abstract: The decision-making for crop planting is key to the efficient and sustainable development of agriculture. Based on the analysis of influencing factors, a multi-objective integer programming model is established, and different planting strategies are proposed under various circumstances using a genetic algorithm for solution. For scenario one, preprocess the data, fill in missing values, and analyze trends. Based on revenue and sustainable planting factors, establish a multi-objective integer programming model, considering factors such as sales volume, costs, yield per mu, prices, and the hazards of repeated cropping. Utilize genetic algorithms to determine the optimal planting strategy for 2024-2030, with an expected maximum profit of 2,049,495.66 yuan during the overproduction and price reduction sales in 2024.For scenario two, based on Situation One, introduce uncertain factors such as cost, sales volume, selling price fluctuations, and weather to optimize the model. Utilize genetic algorithms and Monte Carlo methods for solving, resulting in a new planting decision plan, with an estimated profit of 2,378,465.87 yuan in 2024, an increase of 16% compared to Situation One. For scenario three, analyzing the interrelationships between crops using a complementary substitution matrix of agricultural products, combined with regression analysis to study the correlation between sales, costs, and pricing. Based on this, the model is optimized using genetic algorithms and Monte Carlo methods to derive the optimized planting scheme for 2024-2030, with an estimated profit of 2,593,678.63 yuan in 2024, representing a 9% increase compared to scenario two. Finally, a sensitivity analysis of the model was conducted, and the results indicate that the model possesses good robustness, effectively balancing benefits and sustainable planting needs. Additionally, the advantages and disadvantages of the model were analyzed, and prospects for future applications and improvements were discussed.
Author: Zhichun Wei
Institution: Lanzhou University of Technology
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W4409238691