Author(s)

YanZhuo Wu, GuangWu Ao^*

Affiliation(s)

School of Computer Science and Software Engineering, University of Science and Technology, Anshan 114051, Liaoning, China.

Corresponding Author

GuangWu Ao

ABSTRACT

In order to solve the problems of efficient utilization of limited cultivated land resources and sustainable agricultural development in the North China Plain, this study aims to maximize total profits from 2024-2030, and combines field inspection data to build a planting strategy optimization model. First, the 2023 crop yield per mu and planting area data are processed through the VLOOKUP function to determine the expected future sales volume; the lowest sales price is extracted and profits are calculated based on planting costs. After Python data cleaning and standardization, SPSSPRO is used to visually analyze the profit and income ratio of different plots (flat dry land, terraced fields, etc.) to screen high-quality crops. For the two scenarios of "total waste of excess sales" and "price reduction of excess sales", corresponding objective functions are constructed, constraints such as plot planting cycle, continuous cropping taboos, and bean crop rotation are introduced, and particle swarm optimization (PSO) is used to solve the optimal solution through Python. The results show that the model can effectively balance resource utilization, cost control and ecological constraints, and provide quantitative support for scientific planting decisions in the North China Plain.

KEYWORDS

Particle swarm optimization; Crop planting strategy optimization; North China Plain; Objective function; Cultivated land resource utilization

CITE THIS PAPER

YanZhuo Wu, GuangWu Ao. Crop planting strategies based on particle swarm optimization algorithm. World Journal of Engineering Research. 2025, 3(6): 16-21. DOI: https://doi.org/10.61784/wjer3066.

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