Research on the Optimization of Crop Planting Strategies Based on a Multi-Factor Comprehensive Analysis Model

This paper examines crop planting strategies from 2024 to 2030 in a rural village in the mountainous areas of North China to address the challenges posed by climate change and market volatility. Due to its special geographical location and climatic conditions, crop cultivation in the mountainous areas of North China is susceptible to drought and water shortage, which puts forward higher requirements for the optimization of planting strategies. The study considers two market scenarios: Scenario 1 assumes that the excess crop is completely unsalable, and Scenario 2 considers the excess crop being sold at half price. By simulating market fluctuations through the Monte Carlo algorithm and finding the optimal planting combination combined with the greedy algorithm, this paper seeks the optimal planting plan under different market conditions to maximize the net return. The results show that the optimization strategy can significantly improve the net income of crop planting, reduce the risk caused by market fluctuations, and help promote the sustainable development of rural economy. These optimization strategies have important theoretical and practical significance for improving the economic benefits of crop planting, enhancing the ability of agriculture to resist risks, and promoting the sustainable development of rural economy. Analyzing and optimizing crop planting strategies through scientific methods can not only ensure food security, but also promote agricultural modernization and achieve harmonious development of agriculture and the environment.