This article describes a system that deals with a forest-level bucking optimization problem considering customer's demand and transportation costs. The system was used to evaluate three scenarios: an observed medium-term forest harvesting scenario, with 32 stands harvested during one month, a simulated demand-oriented scenario and a simulated supply-oriented one. Data were obtained from Pinus taeda L. plantations located in southern Brazil. Various forest multiproducts with their respective local market prices were considered for modeling. The system has two main modules: the Cutting Pattern Generation (CPG) and the Global Bucking Optimization (GBO). In both modules, different algorithms are activated depending on the analyzed scenario (demand-oriented or supply-oriented). Additional biometric modules are also integrated into the system for height, taper, and volume calculations. In the demand-oriented scenario, the CPG exhaustively generates all possible cutting patterns for each diametric class in each stand, and the GBO, formulated as a Mixed Integer Linear Programming problem, optimizes the net revenue at forest level subject to constraints that consider bounds for timber volumes and maximum number of different multiproducts obtained in each stand. In the supply-oriented scenario, the CPG generates the Optimum Cutting Pattern through a heuristic algorithm that identifies the potential cuts to evaluate along the stem and a Dynamic Programming-based algorithm to determine the optimum combination of products that maximizes the stem profit, and the GBO calculates the net profit, summing up the profits per stem for each stand and sum of the stands. Illustrative examples and numerical results are given.
