The practice of multicriteria forest management planning is often complicated by the need to explicit a priori goals and preferences of the decisionmaker. This manuscript aims at describing an approach that may take advantage of a posteriori preference modeling to facilitate the specification of the levels of achievement of various objectives in a typical forest management planning framework. The goal is to provide information about nondominated points in the feasible set in the criteria space (FSCS) so that decisionmakers may take advantage of trade-off information. The emphasis is on demonstrating the potential of adaptive search methods to enhance decisions when three or more criteria are considered. The approach combines the use of mathematical programming and interactive decision maps techniques. It is shown how the estimation refinement method may be used to approximate the Pareto frontier of a typical model I linear programming model. It is further shown how the feasible goals method/interactive decision maps method may be used to retrieve a solution selected by stakeholders from interactive decision maps depicting the Pareto frontier. Results are discussed for a large-scale test application encompassing over 1 million ha of cork and holm oak forest ecosystems in southern Portuga
