Optimization of Planting Strategies Based on Dynamic Programming and Monte Carlo Simulation
Year: 2025
Type: article
Abstract: This study uses a combination of dynamic programming and Monte Carlo simulation with the aim of optimizing crop cultivation strategies in a rural village in a mountainous area. First, the optimal cropping scenarios for the years 2024 to 2030 were determined using linear programming for stable economic indicators, and the returns under different scenarios (stagnant sales and discounted sales) were calculated. Secondly, the increasing trend of expected crop sales as well as the volatility were considered, and the forecast of total returns for the next seven years was obtained through dynamic programming and Monte Carlo simulation. Finally, the study introduced the substitutability and complementarity among crops, as well as the correlation between various economic indicators, modified the objective function, and further optimized the planting strategy. The planting scheme proposed through this study not only maximizes economic benefits and minimizes risks in crop cultivation, but also the results of the study will provide a reference for crop cultivation in other regions.
DOI: 10.54097/9bg7mh41
Authors: Yuxin Zhang, Zitong Pan, Tian He
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W4408829031