Author(s)

CongCong Wang^1*, YuLu Ding², XuZhe Chen¹, WeiHao Zhou¹, TianLe Cheng¹

Affiliation(s)

¹School of Mechanical and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, Shandong, China.

²School of Management Engineering, Shandong Jianzhu University, Jinan 250101, Shandong, China.

Corresponding Author

CongCong Wang

ABSTRACT

This study investigates optimal crop planting strategies for a mountainous village in North China during 2024–2030 to maximize profits. Two optimization models were developed for different market scenarios. First, assuming stable market and production parameters, an integer linear programming model is developed to maximize profits while incorporating core agricultural constraints: field type compatibility, crop rotation to avoid replanting, and legume rotation. This model solves for optimal planting schemes under two scenarios: (1) surplus production leading to unsold waste, and (2) surplus sales at a 50% discount. Second, to address uncertainties and potential risks in projected sales volume, yield per mu, planting costs, and sales prices over the coming years, a Monte Carlo model was introduced for analysis. This method simulates fluctuations in parameters (e.g., annual sales growth rate of 5%–10%, yield variation of ±10% per mu) through random sampling, calculates maximum average returns, and thereby determines the optimal planting area allocation scheme with risk resilience in uncertain environments.

KEYWORDS

Crop planting strategy; Integer linear programming; Monte Carlo simulation; Discount

CITE THIS PAPER

CongCong Wang, YuLu Ding, XuZhe Chen, WeiHao Zhou, TianLe Cheng. Optimal crop planting strategies based on integer linear programming and Monte Carlo models. Eurasia Journal of Science and Technology. 2025, 7(6): 18-24. DOI: https://doi.org/10.61784/ejst3120.

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