This work treats a forest planning problem stemming from the daily operation of some large pulp and paper companies. The problem consists in planning and scheduling harvest and transportation activities for each day in a planning horizon of around one year, while satisfying a sizable and complex set of constraints related to the structure of the harvest areas, structure and productivity of the harvest teams, transportation conditions during the rainy seasons, and some properties of the harvested logs. We propose a hybrid approach focused on GRASP (Greedy Randomized Adaptive Search Procedure) metaheuristic and on linear models. Other techniques such as construction based on memory, path-relinking, and recombination methods were used to enhance the basic GRASP procedure. These strategies were tested on real field data and also with some newly generated instances. They proved to be an adequate approach in all cases.