Abstract

The optimization of bucking rules during the forestry harvest is essential for increasing efficiency and profitability. Researchers have explored various taper functions to estimate tree diameters at different heights, which helps generate average tree profiles and assess trunk shape evolution. This study addresses optimizing bucking rules using taper functions to model log shape and maximize the yield from harvested trees. Here, we show that the exponential model is more efficient than the polynomial model regarding raw material utilization and computational time. Compared to previous beliefs, the exponential model does not reach the resolution time limit and demonstrates a steady increase in computational times as the number of logs increases. In contrast, the polynomial model frequently reaches the time limit and shows significant variations in computational times. These findings suggest that the exponential model offers a higher performance in forest resource utilization, which is crucial for the forestry industry's efficiency and cost reduction. Future research could focus on improving and adapting the polynomial model for specific problems, potentially leading to new insights and innovations in forest resource optimization.