Métodos de regulação florestal no planejamento da produção de madeira - Piassi, Ludmila de Castro (2011)
This study aimed to: employ the method of production regulationusing controlper area with the purpose of measuring the annual production capacity of the managed forest; and test the influenceof forest regulation methodsin the planning of wood production.This problem was proposed in a way that it exhibits characteristics similar to those normally found in forestry companies.To characterize the study area,three productive capacities were chosen arbitrarily (siterates I, II and III), plantationsof the Eucalyptusurograndis hybrid, plantation agesvarying from 0 to 7 years and 109 plots.The variables collected were the ones inherent to the productionprocess, such as prices of input, manpower and wood for cellulose. Based on these data, it was obtained the economic rotation for each productive capacity using the Equivalent Periodic Benefit as a criterion for economic evaluation. The optimization models were formulated by Model I, using the SAD Forest software, which allowed generating management prescriptions, as well as creating the optimization model proposed. In the end, five regulatory methodswere evaluated: Method of control per area, Method of control perareaconsidering smaller rotations,Model of linear programming, Modelof integer linear programming and Model of mixed integer linear programming.The method of controlper area was effective in the orientation of determining the restriction limits of imposition of annual productions of the optimization models. The method ofcontrol per area showed the greatest fluctuation in the production and in the annual cutarea.The optimization methods presented the lowest coefficient of variation for the annual wood production. The higher profit was obtained by the method of control per area considering smaller rotations, and it should be viewed with caution, as the obtainedfour years old wood may not have the same value of the one obtained with higher age.The linear programming model had a higher net return than the integer linear programming method, and this fact may be related to regulation restrictions. In the model of mixed integer linear programming, the subdivisions in cutting areas of the plots that allowed this option were disproportionate