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Under compilation: 57(1)

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Silva Fennica 1926-1997
Acta Forestalia Fennica

Articles containing the keyword 'Metropolis algorithm'

Category: Research article

article id 605, category Research article
Paul C. Van Deusen. (2001). Scheduling spatial arrangement and harvest simultaneously. Silva Fennica vol. 35 no. 1 article id 605.
Keywords: simulated annealing; adjacency constraints; Metropolis algorithm
Abstract | View details | Full text in PDF | Author Info
A method based on the Metropolis algorithm is developed for creating desirable spatial configurations on the landscape while simultaneously dealing with other objectives commonly associated with harvest scheduling. Spatial configurations are loosely specified and stochastically attained, which contrasts with other adjacency constraints based on specific block size limits. This method makes it possible to improve habitat and connectivity, and to create buffer zones as part of the scheduling process. It also works with a mapped set of polygons/forest stands and does not require a gridded system.
  • Van Deusen, NCASIS, Northeast Regional Center, 600 Suffolk Street, Fifth Floor, Lowell, MA 01854, USA E-mail: (email)
article id 657, category Research article
Paul C. Van Deusen. (1999). Multiple solution harvest scheduling. Silva Fennica vol. 33 no. 3 article id 657.
Keywords: simulated annealing; Metropolis algorithm; Gibb’s sampler
Abstract | View details | Full text in PDF | Author Info
Application of the Metropolis algorithm for forest harvest scheduling is extended by automating the relative weighting of objective function components. Previous applications of the Metropolis algorithm require the user to specify these weights, which demands substantial trial and error in practice. This modification allows for general incorporation of objective function components that are either periodic or spatial in nature. A generic set of objective function components is developed to facilitate harvest scheduling for a wide range of problems. The resulting algorithm generates multiple feasible solutions rather than a single optimal solution.
  • Van Deusen, Principal Research Scientist, NCASI, Northeast Regional Center, Tufts University, 1 Anderson Hall, Medford, Massachusetts 02155, USA E-mail: (email)

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