Forest planning at the landscape level has the potential to become a large intractable problem. In Finland, Metsähallitus (the state enterprise that manages federally owned land) creates strategic plans to determine the appropriate harvest level. While these plans are feasible, they are not implementable in practice as the harvests are scattered temporally and spatially. Requiring that harvests be organized both temporally and spatially for practical implementation can result in an intractable problem. Through a hierarchical approach, the problem can be organized into steps in which the intractable problem is broken down into smaller easily solvable parts. As an approximation technique, the hierarchical approach may not find a solution close to optimality. To meet this challenge, we combine the top hierarchical level problems with a limited selection of lower hierarchical level problems into a single optimization problem. An iterative process is then used to improve the link between the hierarchical levels. We evaluate the landscape-level management plans developed by the iterative approach with a solution to the complete problem. The iterative process dramatically improves the strategic solution, performing near the global optimum. This suggests that the process can be applied to more computationally challenging problems such as spatial planning and stochastic programming.