Optimal Crop Planting Strategy for a Rural Village Considering Uncertain Factors

Yunze Wang; Jinyi Zhu; Yutong Jiao

doi:10.54097/z6vaf417

Authors

Yunze Wang
Jinyi Zhu
Yutong Jiao

DOI:

https://doi.org/10.54097/z6vaf417

Keywords:

Multi-objective Combinatorial Optimization, Genetic Algorithm, Dynamic Programming Algorithm.

Abstract

With the development of China's crop planting industry and rural economy, it is especially important to improve the planting efficiency. This paper presents a genetic algorithm-based decision model to maximize profits in North China's mountainous crop planting. Through data preprocessing, details about the data can be obtained from the following source: agdata.cn/dataManual/dataTable/MTE5Njkx.html. the median floating unit price is determined, and the planting returns at different times and land types are analyzed to clarify the expected sales volume of each type of crop in 2023. Aiming to maximize profits from 2024 to 2030, an optimization model with 11 constraints is developed. Constraints are simplified using four methods, and a genetic algorithm optimizes the objective function, with dynamic programming enhancing the fitness function to find the best planting strategy. The results of the study provide a scientific basis and decision support for crop cultivation in the mountainous areas of North China, and provide a reference for solving similar problems in other regions, which has important application value.

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