Recently there have been significant changes in the understanding of the forest. Therefore we must add two different interest groups to a new planning proces and also supplement a lot of current data on the state of the forest. Furthermoreit is also necessary to consider an increasingly frequent disturbance changes. Multicriteria optimization methods provide us with a solution for creating a new concept of forest management. These methods can work with different information criterion variables and generate adaptable strategies in risk condotions. The subject of this bachelor theisis is to indicate the work of optimization algorithms needed for tactical and strategic decision – making in forestry. In the first part I describe the decision – making proces and deal with the theoretical knowledge of decision – making. In the second part I devote to the systematic classification of optimization methods. In the third part, I analyze and continuously compare specific stochastic optimization methods with each other, their anvantages and disadvantages along with examples of applications focused on forestry issues.