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Portugal has one of the lowest productivity and performance of operations of forest exploration and vegetation management in Europe. This is mainly due to a mismatch between the equipment used and the geological features of the harvest areas, as well as a lack of communication and technical information about the compatibility of equipment and harvest areas. This dissertation addresses this problem and develops two Mixed Integer Programming (MIP) alternative models that provide a sustainable tactical plan suitable for an ongoing research project at INESC TEC, Project OPTIVEG. The tactical plan schedules the allocation of certain equipment to the different harvest areas in different periods while considering distinct productivity values among different equipment characteristics and area types. To achieve this plan, the problem intends to minimize a set of economic and environmental costs. With the purpose of validating the proposed models, a set of instances was generated, building on data from the project and from similar case studies. Firstly, computational experiments were devised to compare the performance of both models. Afterward, the cost structures of two different spatial layouts of the harvest areas were compared. Finally, sensitivity analyses are performed on the impact of the environmental component of the objective function on the solution. The experiments show that the performance of Model 2 becomes better than Model 1 when instances are larger and that there’s a distinctive change in cost structure when comparing both spatial layouts. Regarding the impact of the environmental objective, considering the price range it is currently applied to, there is little to no influence on the final solution. Furthermore, both models provide a thorough sustainable tactical plan with scheduled equipment allocation to every harvest area considered.