IDEAS home Printed from https://ideas.repec.org/a/eee/forpol/v177y2025ics1389934125001157.html

A Buffered Area Restriction Model (BARM) for optimisation of spatially constrained forest harvest scheduling

Author

Listed:
  • Sacchelli, Sandro
  • Annunziata, Arturo
  • Lapucci, Matteo

Abstract

The paper presents a modified version of Path Formulation for an Area Restriction Model (ARM). The operational research tool automatically constructs suitable buffers among forest unit boundaries to optimise harvesting scheduling in case of management constraints (i.e. maximum adjacent harvested area, green-up age, minimum level of net present value – NPV – to be obtained in different periods etc.). The objective function of the Buffered Area Restriction Model (BARM) is the maximisation of NPV. Economic analysis is developed through an open-source Geographic Information System Decision Support, r.green.biomassfor. The model is tested in a hypothetical forest with scenarios from 30 to 150 forest units. Outputs demonstrate improved optimisation with respect to basic formulation of ARM as well as other models presented in literature. Results show that – in the case study – NPV can reach an improvement of almost 25 % (30 % in a Toy scenario) compared to the base ARM formulation. Highly acceptable errors and resolution times are provided by BARM also in the perspectives of both scientific integration and practical applications. Strengths, weaknesses and potential future improvements of the model are presented.

Suggested Citation

  • Sacchelli, Sandro & Annunziata, Arturo & Lapucci, Matteo, 2025. "A Buffered Area Restriction Model (BARM) for optimisation of spatially constrained forest harvest scheduling," Forest Policy and Economics, Elsevier, vol. 177(C).
  • Handle: RePEc:eee:forpol:v:177:y:2025:i:c:s1389934125001157
    DOI: 10.1016/j.forpol.2025.103536
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1389934125001157
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.forpol.2025.103536?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Billionnet, Alain, 2013. "Mathematical optimization ideas for biodiversity conservation," European Journal of Operational Research, Elsevier, vol. 231(3), pages 514-534.
    2. Hauer, Grant & Cumming, Steve & Schmiegelow, Fiona & Adamowicz, Wiktor & Weber, Marian & Jagodzinski, Robert, 2010. "Tradeoffs between forestry resource and conservation values under alternate policy regimes: A spatial analysis of the western Canadian boreal plains," Ecological Modelling, Elsevier, vol. 221(21), pages 2590-2603.
    3. Sacchelli, Sandro & Cipollaro, Maria & Fabbrizzi, Sara, 2018. "A GIS-based model for multiscale forest insurance analysis: The Italian case study," Forest Policy and Economics, Elsevier, vol. 92(C), pages 106-118.
    4. Teresa Neto & Miguel Constantino & Isabel Martins & João Pedro Pedroso, 2017. "Forest harvest scheduling with clearcut and core area constraints," Annals of Operations Research, Springer, vol. 258(2), pages 453-478, November.
    5. Pra, Alex & Masiero, Mauro & Barreiro, Susana & Tomé, Margarida & Martinez De Arano, Inazio & Orradre, Gabriel & Onaindia, Aitor & Brotto, Lucio & Pettenella, Davide, 2019. "Forest plantations in Southwestern Europe: A comparative trend analysis on investment returns, markets and policies," Forest Policy and Economics, Elsevier, vol. 109(C).
    6. Huizhen Zhang & Miguel Constantino & André Falcão, 2011. "Modeling forest core area with integer programming," Annals of Operations Research, Springer, vol. 190(1), pages 41-55, October.
    7. Isabel Martins & Filipe Alvelos & Miguel Constantino, 2012. "A branch-and-price approach for harvest scheduling subject to maximum area restrictions," Computational Optimization and Applications, Springer, vol. 51(1), pages 363-385, January.
    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. Grilli, Gianluca & Fratini, Roberto & Marone, Enrico & Sacchelli, Sandro, 2020. "A spatial-based tool for the analysis of payments for forest ecosystem services related to hydrogeological protection," Forest Policy and Economics, Elsevier, vol. 111(C).
    10. Alan T. Murray & Ran Wei & Richard L. Church & Matthew R. Niblett, 2019. "Addressing risks and uncertainty in forest land use modeling," Journal of Geographical Systems, Springer, vol. 21(3), pages 319-338, September.
    11. Boston, Kevin & Bettinger, Pete, 2006. "An economic and landscape evaluation of the green-up rules for California, Oregon, and Washington (USA)," Forest Policy and Economics, Elsevier, vol. 8(3), pages 251-266, April.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. 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.
    3. Teresa Neto & Miguel Constantino & Isabel Martins & João Pedro Pedroso, 2017. "Forest harvest scheduling with clearcut and core area constraints," Annals of Operations Research, Springer, vol. 258(2), pages 453-478, November.
    4. Sushil Gupta & Hossein Rikhtehgar Berenji & Manish Shukla & Nagesh N. Murthy, 2023. "Opportunities in farming research from an operations management perspective," Production and Operations Management, Production and Operations Management Society, vol. 32(6), pages 1577-1596, June.
    5. Sandro Sacchelli & Costanza Borghi & Gianluca Grilli, 2021. "Prevention of erosion in mountain basins: A spatial-based tool to support payments for forest ecosystem services," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 67(6), pages 258-271.
    6. 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.
    7. Augustynczik, Andrey Lessa Derci & Yousefpour, Rasoul & Rodriguez, Luiz Carlos Estraviz & Hanewinkel, Marc, 2018. "Conservation Costs of Retention Forestry and Optimal Habitat Network Selection in Southwestern Germany," Ecological Economics, Elsevier, vol. 148(C), pages 92-102.
    8. 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).
    9. 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.
    10. Jiao, Hong-Wei & Liu, San-Yang, 2015. "A practicable branch and bound algorithm for sum of linear ratios problem," European Journal of Operational Research, Elsevier, vol. 243(3), pages 723-730.
    11. 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.
    12. Salgado-Rojas, José & Álvarez-Miranda, Eduardo & Hermoso, Virgilio & Garcia-Gonzalo, Jordi & Weintraub, Andrés, 2020. "A mixed integer programming approach for multi-action planning for threat management," Ecological Modelling, Elsevier, vol. 418(C).
    13. Iritie, Jean-Jacques, 2015. "Economic Growth, Biodiversity and Conservation Policies in Africa: an Overview," MPRA Paper 62005, University Library of Munich, Germany.
    14. 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.
    15. Stephanie A. Snyder & Robert G. Haight, 2016. "Application of the Maximal Covering Location Problem to Habitat Reserve Site Selection," International Regional Science Review, , vol. 39(1), pages 28-47, January.
    16. Grilli, Gianluca & Fratini, Roberto & Marone, Enrico & Sacchelli, Sandro, 2020. "A spatial-based tool for the analysis of payments for forest ecosystem services related to hydrogeological protection," Forest Policy and Economics, Elsevier, vol. 111(C).
    17. Figueroa, Daniela & Galeana-Pizaña, J. Mauricio & Núñez, Juan Manuel & Anzaldo Gómez, Carlos & Hernández-Castro, J. Roberto & Sánchez-Ramírez, María del Mar & Garduño, Andrea, 2021. "Assessing drivers and deterrents of deforestation in Mexico through a public policy tool. The adequacy of the index of economic pressure for deforestation," Forest Policy and Economics, Elsevier, vol. 133(C).
    18. Yang Yi & Mingchang Shi & Jialin Liu & Chen Zhang & Xiaoding Yi & Sha Li & Chunyang Chen & Liangzhao Lin, 2022. "Spatial Distribution of Precise Suitability of Plantation: A Case Study of Main Coniferous Forests in Hubei Province, China," Land, MDPI, vol. 11(5), pages 1-19, May.
    19. Laurent Alfandari & Alborz Hassanzadeh & Ivana Ljubić, 2021. "An Exact Method for Assortment Optimization under the Nested Logit Model," Working Papers hal-02463159, HAL.
    20. Yun, Seong Do & Gramig, Benjamin M., 2014. "Dynamic Optimization of Ecosystem Services: A Comparative Analysis of Non-Spatial and Spatially-Explicit Models," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170450, Agricultural and Applied Economics Association.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:177:y:2025:i:c:s1389934125001157. 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.