Analysis of Uncertainty of Future Timber Yields in Forest Management
We consider the effect that the uncertainty of future yields has on forest management. One way of modeling this problem is through chance constrained linear programming, where constraints are represented as probabilistic statements. Under normality conditions, an equivalent deterministic nonlinear program can be solved in an efficient way using a cutting plane algorithm, which takes advantage of the characteristics of the problem. To deal with uncertainty, we propose a forest planning approach, based on chance constrained linear programming. We also analyze the importance of including the consideration of uncertainty in the planning process. For this purpose, we simulate two scenarios, a deterministic one and another where uncertainty is included in the models. Results of a test case show that not considering uncertainty in the models when production demand constraints have small slack can lead to management situations with infeasible solutions. For. Sci. 41(2):217-234.
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Document Type: Journal Article
Affiliations: Department of Industrial Engineering, Universidad de Chile, Republica 701, Casilla 2777, Santiago, Chile
Publication date: 1995-05-01
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- Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
Forest Science is published bimonthly in February, April, June, August, October, and December.
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