Abstract
Today, forest management has become an arduous task. Forests are managed for efficient timber production, which demands large uniform stands, as well as for conservation and recreation, which require a pattern of smaller, more diverse stands. The forest management problem can therefore be regarded as an optimal patch design problem. In this chapter, the potential use of probabilistic models for linkage learning is investigated in the field of optimal patch design. The following hypothesis is investigated: linkage learning helps to solve the forest management problem and results in significantly better solutions. Two linkage learning algorithms and a simple genetic algorithm are compared and possible differences are explained in the context of this optimization problem.
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