Optimizing forest planning: Balancing timber production and carbon sequestration through a multi-objective disjunctive formulation

Autores
Piedra Jimenez, Frank Cecilio; Broz, Diego Ricardo; Novas, Juan Matias; Grossmann, Ignacio E.; Rodriguez, Maria Analia
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This work introduces a multi-objective model for the Forest Planning Problem (FPP), designed to optimize forest management by determining the best combination of silvicultural treatments, land harvesting proportions, net carbon sequestration, and timber flow. Using Generalized Disjunctive Programming (GDP), the model addresses two conflicting objectives: maximizing net present value and maximizing 2 sequestration, while accounting for carbon sequestration losses from third parties. The model is reformulated as a mixed-integer linear programming (MILP) problem using both Hull reformulation and Big-M reformulation and validated with data from a forest company in Misiones, Argentina. Results show that increasing forest area reduces reliance on external timber, and that stand characteristics and diverse prescriptions are more effective for improving 2 sequestration than simply expanding forest area. Additionally, the Hull reformulation proves more robust for complex problems, while Big-M is advantageous for simpler cases.
Fil: Piedra Jimenez, Frank Cecilio. Universidad Nacional de Córdoba. Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada; Argentina
Fil: Broz, Diego Ricardo. Universidad Nacional de Misiones. Facultad de Ciencias Forestales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Novas, Juan Matias. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina
Fil: Grossmann, Ignacio E.. University of Carnegie Mellon. Department of Chemical Engineering; Estados Unidos
Fil: Rodriguez, Maria Analia. Universidad Nacional de Córdoba. Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada; Argentina
Materia
SPATIAL FORESTRY PLANNING
CARBON SEQUESTRATION
INDUSTRIAL FOREST PLANTATIONS
GENERALIZED DISJUNCTIVE PROGRAMMING
MULTI-OBJECTIVE OPTIMIZATION
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/273888
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Optimizing forest planning: Balancing timber production and carbon sequestration through a multi-objective disjunctive formulationPiedra Jimenez, Frank CecilioBroz, Diego RicardoNovas, Juan MatiasGrossmann, Ignacio E.Rodriguez, Maria AnaliaSPATIAL FORESTRY PLANNINGCARBON SEQUESTRATIONINDUSTRIAL FOREST PLANTATIONSGENERALIZED DISJUNCTIVE PROGRAMMINGMULTI-OBJECTIVE OPTIMIZATIONhttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2This work introduces a multi-objective model for the Forest Planning Problem (FPP), designed to optimize forest management by determining the best combination of silvicultural treatments, land harvesting proportions, net carbon sequestration, and timber flow. Using Generalized Disjunctive Programming (GDP), the model addresses two conflicting objectives: maximizing net present value and maximizing 2 sequestration, while accounting for carbon sequestration losses from third parties. The model is reformulated as a mixed-integer linear programming (MILP) problem using both Hull reformulation and Big-M reformulation and validated with data from a forest company in Misiones, Argentina. Results show that increasing forest area reduces reliance on external timber, and that stand characteristics and diverse prescriptions are more effective for improving 2 sequestration than simply expanding forest area. Additionally, the Hull reformulation proves more robust for complex problems, while Big-M is advantageous for simpler cases.Fil: Piedra Jimenez, Frank Cecilio. Universidad Nacional de Córdoba. Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada; ArgentinaFil: Broz, Diego Ricardo. Universidad Nacional de Misiones. Facultad de Ciencias Forestales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Novas, Juan Matias. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; ArgentinaFil: Grossmann, Ignacio E.. University of Carnegie Mellon. Department of Chemical Engineering; Estados UnidosFil: Rodriguez, Maria Analia. Universidad Nacional de Córdoba. Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada; ArgentinaElsevier Science2025-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/273888Piedra Jimenez, Frank Cecilio; Broz, Diego Ricardo; Novas, Juan Matias; Grossmann, Ignacio E.; Rodriguez, Maria Analia; Optimizing forest planning: Balancing timber production and carbon sequestration through a multi-objective disjunctive formulation; Elsevier Science; Forest Policy And Economics; 178; 2-2025; 1-401389-9341CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.forpol.2025.103575info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S1389934125001546info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-11-26T08:52:03Zoai:ri.conicet.gov.ar:11336/273888instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-11-26 08:52:04.003CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Optimizing forest planning: Balancing timber production and carbon sequestration through a multi-objective disjunctive formulation
title Optimizing forest planning: Balancing timber production and carbon sequestration through a multi-objective disjunctive formulation
spellingShingle Optimizing forest planning: Balancing timber production and carbon sequestration through a multi-objective disjunctive formulation
Piedra Jimenez, Frank Cecilio
SPATIAL FORESTRY PLANNING
CARBON SEQUESTRATION
INDUSTRIAL FOREST PLANTATIONS
GENERALIZED DISJUNCTIVE PROGRAMMING
MULTI-OBJECTIVE OPTIMIZATION
title_short Optimizing forest planning: Balancing timber production and carbon sequestration through a multi-objective disjunctive formulation
title_full Optimizing forest planning: Balancing timber production and carbon sequestration through a multi-objective disjunctive formulation
title_fullStr Optimizing forest planning: Balancing timber production and carbon sequestration through a multi-objective disjunctive formulation
title_full_unstemmed Optimizing forest planning: Balancing timber production and carbon sequestration through a multi-objective disjunctive formulation
title_sort Optimizing forest planning: Balancing timber production and carbon sequestration through a multi-objective disjunctive formulation
dc.creator.none.fl_str_mv Piedra Jimenez, Frank Cecilio
Broz, Diego Ricardo
Novas, Juan Matias
Grossmann, Ignacio E.
Rodriguez, Maria Analia
author Piedra Jimenez, Frank Cecilio
author_facet Piedra Jimenez, Frank Cecilio
Broz, Diego Ricardo
Novas, Juan Matias
Grossmann, Ignacio E.
Rodriguez, Maria Analia
author_role author
author2 Broz, Diego Ricardo
Novas, Juan Matias
Grossmann, Ignacio E.
Rodriguez, Maria Analia
author2_role author
author
author
author
dc.subject.none.fl_str_mv SPATIAL FORESTRY PLANNING
CARBON SEQUESTRATION
INDUSTRIAL FOREST PLANTATIONS
GENERALIZED DISJUNCTIVE PROGRAMMING
MULTI-OBJECTIVE OPTIMIZATION
topic SPATIAL FORESTRY PLANNING
CARBON SEQUESTRATION
INDUSTRIAL FOREST PLANTATIONS
GENERALIZED DISJUNCTIVE PROGRAMMING
MULTI-OBJECTIVE OPTIMIZATION
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This work introduces a multi-objective model for the Forest Planning Problem (FPP), designed to optimize forest management by determining the best combination of silvicultural treatments, land harvesting proportions, net carbon sequestration, and timber flow. Using Generalized Disjunctive Programming (GDP), the model addresses two conflicting objectives: maximizing net present value and maximizing 2 sequestration, while accounting for carbon sequestration losses from third parties. The model is reformulated as a mixed-integer linear programming (MILP) problem using both Hull reformulation and Big-M reformulation and validated with data from a forest company in Misiones, Argentina. Results show that increasing forest area reduces reliance on external timber, and that stand characteristics and diverse prescriptions are more effective for improving 2 sequestration than simply expanding forest area. Additionally, the Hull reformulation proves more robust for complex problems, while Big-M is advantageous for simpler cases.
Fil: Piedra Jimenez, Frank Cecilio. Universidad Nacional de Córdoba. Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada; Argentina
Fil: Broz, Diego Ricardo. Universidad Nacional de Misiones. Facultad de Ciencias Forestales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Novas, Juan Matias. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina
Fil: Grossmann, Ignacio E.. University of Carnegie Mellon. Department of Chemical Engineering; Estados Unidos
Fil: Rodriguez, Maria Analia. Universidad Nacional de Córdoba. Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada; Argentina
description This work introduces a multi-objective model for the Forest Planning Problem (FPP), designed to optimize forest management by determining the best combination of silvicultural treatments, land harvesting proportions, net carbon sequestration, and timber flow. Using Generalized Disjunctive Programming (GDP), the model addresses two conflicting objectives: maximizing net present value and maximizing 2 sequestration, while accounting for carbon sequestration losses from third parties. The model is reformulated as a mixed-integer linear programming (MILP) problem using both Hull reformulation and Big-M reformulation and validated with data from a forest company in Misiones, Argentina. Results show that increasing forest area reduces reliance on external timber, and that stand characteristics and diverse prescriptions are more effective for improving 2 sequestration than simply expanding forest area. Additionally, the Hull reformulation proves more robust for complex problems, while Big-M is advantageous for simpler cases.
publishDate 2025
dc.date.none.fl_str_mv 2025-02
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/273888
Piedra Jimenez, Frank Cecilio; Broz, Diego Ricardo; Novas, Juan Matias; Grossmann, Ignacio E.; Rodriguez, Maria Analia; Optimizing forest planning: Balancing timber production and carbon sequestration through a multi-objective disjunctive formulation; Elsevier Science; Forest Policy And Economics; 178; 2-2025; 1-40
1389-9341
CONICET Digital
CONICET
url http://hdl.handle.net/11336/273888
identifier_str_mv Piedra Jimenez, Frank Cecilio; Broz, Diego Ricardo; Novas, Juan Matias; Grossmann, Ignacio E.; Rodriguez, Maria Analia; Optimizing forest planning: Balancing timber production and carbon sequestration through a multi-objective disjunctive formulation; Elsevier Science; Forest Policy And Economics; 178; 2-2025; 1-40
1389-9341
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.forpol.2025.103575
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S1389934125001546
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1849872897146880000
score 13.011256

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