Review of a Linear Programming Model for Forest Management Introducing Integer, Multiobjective, and Stochastic Formulations

This article revises a linear programming model for forest production in Ceará. After correcting inconsistencies in the original deterministic baselines, the study integrates mixed-integer (MILP), multiobjective (MOO), and two-stage stochastic formulations. The MILP validates discrete lot selections under strict constraints. The MOO maps the environmental trade-off, demonstrating that pure profit maximization disproportionately increases ecological penalties. Finally, the stochastic model mitigates operational uncertainty, optimizing expected net profit by anticipating recourse costs for resource shortages. These extensions offer a robust, realistic  alternative to the original profit-exclusive framework.