Research on optimal planting strategy risk based on Monte Carlo method

Abstract

With the increasing uncertainties posed by global climate change, frequent natural disasters, and market fluctuations, along with evolving policy changes, crop cultivation is encountering an array of risks and challenges. While risk factors associated with crop growth and marketing have been extensively studied over the years, there remains a significant gap in research focused on developing optimal planting programs that effectively incorporate these risk factors. This paper addresses this gap by utilizing an open data set as a case study. It draws upon existing planting schemes and sets annual profit maximization as its primary objective. By integrating the Monte Carlo method, the research aims to formulate a sustainable planting strategy that consistently enhances annual profits despite prevailing uncertainties. The proposed planting strategy not only minimizes potential losses arising from various risks faced during the planting and marketing processes but also enhances production efficiency. Furthermore, it contributes to the overall development of agricultural production by fostering resilience against unpredictable challenges. This approach not only supports farmers in making informed decisions about their planting schedules and crop selections but also promotes long-term sustainability in agricultural practices. Ultimately, the findings of this research hold the potential to significantly benefit both individual farmers and the broader agricultural sector.