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A Comparison of the Pattern Search Algorithm and the Modified PATH Algorithm for Optimizing an Individual Tree Model

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A new stand-level dynamic programming algorithm was developed for determining the optimal residual diameter distribution for multiple stand entries. The proposed algorithm consists of the PATH algorithm and the concept of region-limiting strategies and iterated dynamic programming. Employing the proposed algorithm, a dynamic programming model was constructed with the Stand Prognosis Model, a single-tree/distance-independent growth model for forest types in the northern Rocky Mountains. Convergence, accuracy, and efficiency of the algorithm are discussed in comparison with a nonlinear programming algorithm, the Hooke and Jeeves method. For problems with three or more thinnings, the proposed algorithm yielded superior solutions with less computation time than did the Hooke and Jeeves method. For one and two thinning problems, the Hooke and Jeeves method provided better solutions. The advantage of the proposed algorithm stems from the ability of dynamic programming approaches to avoid including multiple partial local optima in the solution, and a clearer relationship to established principles of concave optimization. For. Sci. 36(2):394-412.

Keywords: Operations research; dynamic programming; forest economics

Document Type: Journal Article

Affiliations: Professor, Department of Forest Resources, Oregon State University, Corvallis, OR 97331

Publication date: June 1, 1990

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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