A Model For Recognizing Forestwide Risk in Timber Management Scheduling
Abstract:This paper presents one method of recognizing risk in formulating and solving timber management scheduling problems. Emphasis is given to developing a schedule for the short run that will perform well over a range of plausible future conditions. The method merges linear programming formulations for specific scenarios describing the future. Separate schedules are determined for each scenario with the added requirement that all of the schedules are identical for the short run. This formulation is shown to be a simplified form of the multistage recourse problem as described by Dantzig (1963). The solution technique developed by Hoganson and Rose (1984) is proposed as a possible solution technique. This technique decomposes the problem into subproblems of manageable size. The subproblems are simply decision-tree problems describing options for individual stand types, with specific branches of the trees representing stochastic elements of the problem. The key to the solution process is the interpretation and predictability of the key dual variables of the formulation. A large-scale example is given, and results are examined to consider how methods might be refined to better deal with uncertainty. For. Sci. 33(2):268-282.
Document Type: Journal Article
Affiliations: Professor, College of Forestry, University of Minnesota
Publication date: 1987-06-01
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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.
2015 Impact Factor: 1.702
Ranking: 16 of 66 in forestry
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