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Stochastic optimization models in forest planning: a progressive hedging solution approach

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  • Fernando Veliz
  • Jean-Paul Watson
  • Andres Weintraub
  • Roger Wets
  • David Woodruff

Abstract

We consider the important problem of medium term forest planning with an integrated approach considering both harvesting and road construction decisions in the presence of uncertainty modeled as a multi-stage problem. We give strengthening methods that enable the solution of problems with many more scenarios than previously reported in the literature. Furthermore, we demonstrate that a scenario-based decomposition method (Progressive Hedging) is competitive with direct solution of the extensive form, even on a serial computer. Computational results based on a real-world example are presented. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Fernando Veliz & Jean-Paul Watson & Andres Weintraub & Roger Wets & David Woodruff, 2015. "Stochastic optimization models in forest planning: a progressive hedging solution approach," Annals of Operations Research, Springer, vol. 232(1), pages 259-274, September.
    • Handle: RePEc:spr:annopr:v:232:y:2015:i:1:p:259-274:10.1007/s10479-014-1608-4
    DOI: 10.1007/s10479-014-1608-4
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    References listed on IDEAS

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    4. Alonso-Ayuso, Antonio & Escudero, Laureano F. & Guignard, Monique & Weintraub, Andres, 2018. "Risk management for forestry planning under uncertainty in demand and prices," European Journal of Operational Research, Elsevier, vol. 267(3), pages 1051-1074.
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    6. Nader Naderializadeh & Kevin A. Crowe & Melika Rouhafza, 2022. "Solving the integrated forest harvest scheduling model using metaheuristic algorithms," Operational Research, Springer, vol. 22(3), pages 2437-2463, July.
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    8. Gomes, Vanessa de Souza & Monti, Cássio Augusto Ussi & Silva, Carolina Souza Jarochinski e & Gomide, Lucas Rezende, 2021. "Operational harvest planning under forest road maintenance uncertainty," Forest Policy and Economics, Elsevier, vol. 131(C).

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