IDEAS home Printed from https://ideas.repec.org/a/eee/forpol/v103y2019icp112-122.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S138993411630346X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.forpol.2018.03.006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Belaid Aouni & Fouad Ben Abdelaziz & Davide La Torre, 2012. "The stochastic goal programming model: Theory and applications," Post-Print hal-00778729, HAL.
    2. Billionnet, Alain, 2013. "Mathematical optimization ideas for biodiversity conservation," European Journal of Operational Research, Elsevier, vol. 231(3), pages 514-534.
    3. 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.
    4. 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.
    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. 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.
    7. Ballestero, Enrique, 2001. "Stochastic goal programming: A mean-variance approach," European Journal of Operational Research, Elsevier, vol. 131(3), pages 476-481, June.
    8. 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.
    9. Bruno Contini, 1968. "A Stochastic Approach to Goal Programming," Operations Research, INFORMS, vol. 16(3), pages 576-586, June.
    10. 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.
    11. 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.
    12. Abdelaziz, Fouad Ben, 2012. "Solution approaches for the multiobjective stochastic programming," European Journal of Operational Research, Elsevier, vol. 216(1), pages 1-16.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Álvarez-Miranda, Eduardo & Garcia-Gonzalo, Jordi & Ulloa-Fierro, Felipe & Weintraub, Andrés & Barreiro, Susana, 2018. "A multicriteria optimization model for sustainable forest management under climate change uncertainty: An application in Portugal," European Journal of Operational Research, Elsevier, vol. 269(1), pages 79-98.
    2. Irfan Ali & Umar Muhammad Modibbo & Jahangir Chauhan & Maryam Meraj, 2021. "An integrated multi-objective optimization modelling for sustainable development goals of India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(3), pages 3811-3831, March.
    3. Mikael Rönnqvist & Sophie D’Amours & Andres Weintraub & Alejandro Jofre & Eldon Gunn & Robert Haight & David Martell & Alan Murray & Carlos Romero, 2015. "Operations Research challenges in forestry: 33 open problems," Annals of Operations Research, Springer, vol. 232(1), pages 11-40, September.
    4. Raja Jayaraman & Cinzia Colapinto & Danilo Liuzzi & Davide Torre, 2017. "Planning sustainable development through a scenario-based stochastic goal programming model," Operational Research, Springer, vol. 17(3), pages 789-805, October.
    5. Zhongfeng Qin, 2018. "Uncertain random goal programming," Fuzzy Optimization and Decision Making, Springer, vol. 17(4), pages 375-386, December.
    6. Sinha, Ankur & Rämö, Janne & Malo, Pekka & Kallio, Markku & Tahvonen, Olli, 2017. "Optimal management of naturally regenerating uneven-aged forests," European Journal of Operational Research, Elsevier, vol. 256(3), pages 886-900.
    7. Ran Wei & Alan Murray, 2015. "Spatial uncertainty in harvest scheduling," Annals of Operations Research, Springer, vol. 232(1), pages 275-289, September.
    8. Augustynczik, A.L.D. & Arce, J.E. & Silva, A.C.L., 2016. "Aggregating forest harvesting activities in forest plantations through Integer Linear Programming and Goal Programming," Journal of Forest Economics, Elsevier, vol. 24(C), pages 72-81.
    9. Muñoz, María M. & Abdelaziz, Fouad Ben, 2012. "Satisfactory solution concepts and their relations for Stochastic Multiobjective Programming problems," European Journal of Operational Research, Elsevier, vol. 220(2), pages 430-442.
    10. Minas, James P. & Hearne, John W. & Martell, David L., 2014. "A spatial optimisation model for multi-period landscape level fuel management to mitigate wildfire impacts," European Journal of Operational Research, Elsevier, vol. 232(2), pages 412-422.
    11. Kıbış, Eyyüb Y. & Büyüktahtakın, İ. Esra, 2017. "Optimizing invasive species management: A mixed-integer linear programming approach," European Journal of Operational Research, Elsevier, vol. 259(1), pages 308-321.
    12. Billionnet, Alain, 2013. "Mathematical optimization ideas for biodiversity conservation," European Journal of Operational Research, Elsevier, vol. 231(3), pages 514-534.
    13. Álvarez-Miranda, Eduardo & Goycoolea, Marcos & Ljubić, Ivana & Sinnl, Markus, 2021. "The Generalized Reserve Set Covering Problem with Connectivity and Buffer Requirements," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1013-1029.
    14. Oğuzhan Ahmet Arık, 2021. "Long-term Plantation and Harvesting Planning for Industrial Plantation Forest Areas," SN Operations Research Forum, Springer, vol. 2(2), pages 1-23, June.
    15. Abdelaziz, Fouad Ben, 2012. "Solution approaches for the multiobjective stochastic programming," European Journal of Operational Research, Elsevier, vol. 216(1), pages 1-16.
    16. Masri, Hatem & Abdulla, Yomna, 2018. "A multiple objective stochastic programming model for working capital management," Technological Forecasting and Social Change, Elsevier, vol. 131(C), pages 141-146.
    17. Andrés Weintraub & Carlos Romero, 2006. "Operations Research Models and the Management of Agricultural and Forestry Resources: A Review and Comparison," Interfaces, INFORMS, vol. 36(5), pages 446-457, October.
    18. 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.
    19. Pascual, Adrián & Guerra-Hernández, Juan, 2022. "Spatial connectivity in tree-level decision-support models using mathematical optimization and individual tree mapping," Forest Policy and Economics, Elsevier, vol. 139(C).
    20. Constantino, Miguel & Martins, Isabel, 2018. "Branch-and-cut for the forest harvest scheduling subject to clearcut and core area constraints," European Journal of Operational Research, Elsevier, vol. 265(2), pages 723-734.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:forpol:v:103:y:2019:i:c:p:112-122. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/forpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.