Data-Based Forest Management with Uncertainties and Multiple Objectives
In this paper, we present an approach of employing multiobjective optimization to support decision making in forest management planning. The planning is based on data representing so-called stands, each consisting of homogeneous parts of the forest, and simulations of how the trees grow in the stands under different treatment options. Forest planning concerns future decisions to be made that include uncertainty. We employ as objective functions both the expected values of incomes and biodiversity as well as the value at risk for both of these objectives. In addition, we minimize the risk level for both the income value and the biodiversity value. There is a tradeoff between the expected value and the value at risk, as well as between the value at risk of the two objectives of interest and, thus, decision support is needed to find the best balance between the conflicting objectives. We employ an interactive method where a decision maker iteratively provides preference information to find the most preferred management plan and at the same time learns about the interdependencies of the objectives.
KeywordsForest management planning Multiobjective optimization Interactive multiobjective optimization Pareto optimality Uncertainty
We acknowledge Natural Resources Institute Finland Luke (for the MS-NFI data) and the Finish Research Institute VTT (for the segmentation). In addition, we thank IBM for allowing IBM® ILOG® CPLEX® Optimization Studio being used for academic work through the Academic initiative.
- Eyvindson, K., Kangas, A.: Evaluating the required scenario set size for stochastic programming in forest management planning: incorporating inventory and growth model uncertainty. Can. J. For. Sci. 46(3), 340–347 (2016a)Google Scholar
- Kangas, A., Kurttila, M., Hujala, T., Eyvindson, K., Kangas, J.: Decision Support for Forest Management. Managing forest ecosystems, 2nd edn., vol. 30. 307 p. Springer, New York (2005)Google Scholar
- Miettinen, K.: Nonlinear Multiobjective Optimization, 298 p. Kluwer, Boston (1999)Google Scholar
- Pykäläinen, J.: Interactive use of multi-criteria decision analysis in forest planning. Dissertation. Faculty of Forestry, University of Joensuu (2000)Google Scholar
- Tomppo, E.: Keski-Suomen metsäkeskuksen alueen metsävarat ja niiden kehitys 1967–96. Metsätieteen aikakauskirja 2B/1999, pp. 309–387 (1999). (in Finnish)Google Scholar
- Wierzbicki, A.P.: Reference point approaches. In: Gal, T., Stewart, T.J., Hanne, T. (eds.) Multicriteria Decision Making: Advances in MCDM Models, Algorithms, Theory, and Applications, pp. 9-1–9-39. Kluwer Academic Publishers, Boston (1999)Google Scholar