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Estimating Optimal Thinning and Rotation for Mixed-Species Timber Stands Using a Random Search Algorithm

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Abstract:

The problem of optimal density over time for even-aged, mixed-species stands is formulated as a nonlinear-integer programming problem with numbers of trees cut by species and diameter class as decision variables. The model is formulated using a stand-table projection growth model to predict mixed-species growth and stand-structure. Optimal thinning and final harvest age are estimated simultaneously using heuristic random search algorithms. For sample problems with two species, random search methods provide near-optimal cutting strategies with very little computer time or memory. Optimal solutions are estimated for problems with eight initial species/diameter class groups, projected for up to three discrete growth periods. Such solution methods merit further study for evaluating complex stand- and forest-level decisions. Forest Sci. 31:303-315.

Keywords: Combinatorial optimization; heuristics; integer programming; nonlinear programming; random search; stand-level optimization; stand-table projection

Document Type: Journal Article

Affiliations: Associate Professor, Forest Economics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061

Publication date: June 1, 1985

More about this publication?
  • 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

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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