Global Meritorious Winner — Top ~10% among 11,296 teams. The only high school team to achieve this on Problem B (among 728 teams).
Methodology
We first built an optimization model by subtracting the predicted economic profit using the modeled negative impacts, and conducted simulated annealing to obtain the value of each variable for the optimized policy.
To account for changes in animal populations and propose an alternative policy that preserves these populations, we developed our animal population model using the logistic model framework. This model includes the additional mortality rate resulting from policies that permit hunting.
We converted the differential equation into a recursive form using the Euler Method to solve it. To estimate the natural growth rates of various animals within the national reserve, we employed an exponential growth model, aligning it with the existing population data. The main model was refined by incorporating a constraint derived from the differential equation.