Optimal crop planting strategies based on multi-objective planning and Monte Carlo algorithm
Cong Cai · Information Systems and Economics · 2024
This paper solves the problem of how to plan the crop planting programme from 2024 to 2030 in order to get the highest total return, using dynamic planning as the basic method, applying the idea of greedy algorithm, each year based on the prediction of the previous year to formulate the decision of the current year, and constructing and solving the multi-stage planning model for the two treatments of the stagnant portion of the optimal decision-making for the period of 2024 to 2030 respectively. The optimal decision for 2024 to 2030 was obtained. At the same time, various potential planting risks such as past sales experience, expected sales volume of various crops, mu yield, planting cost and uncertainty of sales price were considered, and each parameter may be different at different times. In view of the above uncertainties, this paper adopts Monte Carlo algorithm and probabilistic statistical method to simulate the problem in different scenarios, and obtains the expected value of the problem through a large number of random samples sampling to enhance the planting programme's risk-resistant ability.