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A multicriteria stochastic optimization framework for sustainable forest decision making under uncertainty

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  • Álvarez-Miranda, Eduardo
  • Garcia-Gonzalo, Jordi
  • Pais, Cristobal
  • Weintraub, Andrés

Abstract

A core process in forestry planning corresponds to the design of optimal harvesting policies along with road network layouts. In the most common setting, decision makers seek for solutions that maximize the profit of the forest while respecting operative and market constraints. Due to the long-term nature of the industry, the inherent uncertainty in both forest growth and market conditions should be taken into account. Nowadays, forest planning must target towards a sustainable management; the maximization of carbon sequestration and the minimization of land erosion are two common environmental goals.

Suggested Citation

  • Álvarez-Miranda, Eduardo & Garcia-Gonzalo, Jordi & Pais, Cristobal & Weintraub, Andrés, 2019. "A multicriteria stochastic optimization framework for sustainable forest decision making under uncertainty," Forest Policy and Economics, Elsevier, vol. 103(C), pages 112-122.
    • Handle: RePEc:eee:forpol:v:103:y:2019:i:c:p:112-122
    DOI: 10.1016/j.forpol.2018.03.006
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    References listed on IDEAS

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    1. Billionnet, Alain, 2013. "Mathematical optimization ideas for biodiversity conservation," European Journal of Operational Research, Elsevier, vol. 231(3), pages 514-534.
    2. Kangas, Annika S. & Kangas, Jyrki, 2004. "Probability, possibility and evidence: approaches to consider risk and uncertainty in forestry decision analysis," Forest Policy and Economics, Elsevier, vol. 6(2), pages 169-188, March.
    3. Rodolfo Carvajal & Miguel Constantino & Marcos Goycoolea & Juan Pablo Vielma & Andrés Weintraub, 2013. "Imposing Connectivity Constraints in Forest Planning Models," Operations Research, INFORMS, vol. 61(4), pages 824-836, August.
    4. Abdelaziz, Fouad Ben, 2012. "Solution approaches for the multiobjective stochastic programming," European Journal of Operational Research, Elsevier, vol. 216(1), pages 1-16.
    5. Antonio Alonso-Ayuso & Laureano Escudero & Monique Guignard & Martín Quinteros & Andres Weintraub, 2011. "Forestry management under uncertainty," Annals of Operations Research, Springer, vol. 190(1), pages 17-39, October.
    6. Belaid Aouni & Fouad Ben Abdelaziz & Davide La Torre, 2012. "The stochastic goal programming model: Theory and applications," Post-Print hal-00778729, HAL.
    7. Krcmar, Emina & Stennes, Brad & Cornelis van Kooten, G. & Vertinsky, Ilan, 2001. "Carbon sequestration and land management under uncertainty," European Journal of Operational Research, Elsevier, vol. 135(3), pages 616-629, December.
    8. Ballestero, Enrique, 2001. "Stochastic goal programming: A mean-variance approach," European Journal of Operational Research, Elsevier, vol. 131(3), pages 476-481, June.
    9. Marcos Goycoolea & Alan T. Murray & Francisco Barahona & Rafael Epstein & Andrés Weintraub, 2005. "Harvest Scheduling Subject to Maximum Area Restrictions: Exploring Exact Approaches," Operations Research, INFORMS, vol. 53(3), pages 490-500, June.
    10. Bruno Contini, 1968. "A Stochastic Approach to Goal Programming," Operations Research, INFORMS, vol. 16(3), pages 576-586, June.
    11. Andres Weintraub & Richard Church & Alan Murray & Monique Guignard, 2000. "Forest management models and combinatorial algorithms: analysis of state of the art," Annals of Operations Research, Springer, vol. 96(1), pages 271-285, November.
    12. Martell, David L. & Gunn, Eldon A. & Weintraub, Andres, 1998. "Forest management challenges for operational researchers," European Journal of Operational Research, Elsevier, vol. 104(1), pages 1-17, January.
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    Cited by:

    1. Félix Bastit & Marielle Brunette & Claire Montagne-Huck, 2021. "Earth, wind and fire: A multi-hazard risk review for natural disturbances in forests," Working Papers of BETA 2021-25, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    2. 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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