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An Application of a Reduced Cost Approach to Spatial Forest Planning

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The task of forest planning is to find the best combination of treatment schedules for forest stands. With many stands and several alternatives per stand the number of possible combinations becomes very large and standard heuristics for combinatorial optimization such as simulated annealing (SA), tabu search, and genetic algorithm become slow. One way to deal with the problem of large decision space is to decompose the forest-level problem into stand-level subproblems. We developed a spatial application of the decomposing technique proposed by Hoganson and Rose. This method maximizes the reduced cost (RC) of each stand. The dual prices of forest-level constraints appear in the RC function and they tie the stand-level problems together. In our spatial application of the RC method we used a multiobjective stand-level objective function. The function included spatial objective variables, the values of which depended on adjacent stands. The dual prices of nonspatial forest-level constraints were gradually adjusted by using a variant of the subgradient method, until the set of stand-level solutions fulfilled the forest-level constraints. The method was compared with a cellular automaton and the SA heuristic in a spatial problem in two different forests. The results suggest that the spatial application of the RC method is competitive with heuristics currently used in forest planning. It was slightly superior to SA in terms of the objective function value of SA. The method is easy to use because it has few parameters.
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Keywords: Lagrangean relaxation; cellular automata; dual prices; dual problem; linear programming; simulated annealing; spatial optimization

Document Type: Research Article

Publication date: 2009-02-01

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.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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