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Searching for sustainable national forest harvest levels through interactive multiobjective optimization.

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Τίτλος: Searching for sustainable national forest harvest levels through interactive multiobjective optimization.
Συγγραφείς: Saini, Bhupinder Singh1 (AUTHOR) bhupinder.s.saini@jyu.fi, Kangas, Annika2 (AUTHOR), Mehtätalo, Lauri2 (AUTHOR), Hirvelä, Hannu3 (AUTHOR), Shavazipour, Babooshka1 (AUTHOR), Miettinen, Kaisa4 (AUTHOR)
Πηγή: Canadian Journal of Forest Research. 5/12/2026, Vol. 56, p1-13. 13p.
Θεματικοί όροι: *Multi-objective optimization, *Linear programming, *Decision support systems, *Forest management, *Automated planning & scheduling, *Logging
Γεωγραφικοί όροι: Finland
Περίληψη: In Finland, linear optimization has been used to search for sustainable national harvest levels for over 30 years—commonly maximizing net present value from forests county by county, while ensuring sustainability of wood production by requiring nondecreasing harvest levels over time. However, this approach does not help policymakers understand how the selected harvest level is reached and what affects the result. Moreover, optimizing per county may lead to an inefficient solution, as the counties serve as constraints. National-level interactive planning is a better approach, but such interactive optimization is compute-intensive. We present an interactive multiobjective optimization approach applying the NAUTILUS Navigator method. It is based on precalculated optimal solutions and gradual improvements from the nadir (the worst solution). We apply the approach in a novel way: starting with a sparse representation of optimal solutions and generating a denser representation in the area of interest, saving computational resources. The problem formulation is also improved during the solution process. Moreover, the interactive approach advises decision makers on the consequences of the selected solution better than a few preselected scenarios. The decision maker can direct the solution process and find preferred solutions. The results also show improvement in solutions when the county-level constraints are removed. [ABSTRACT FROM AUTHOR]
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  Data: Searching for sustainable national forest harvest levels through interactive multiobjective optimization.
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  Data: <searchLink fieldCode="JN" term="%22Canadian+Journal+of+Forest+Research%22">Canadian Journal of Forest Research</searchLink>. 5/12/2026, Vol. 56, p1-13. 13p.
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  Data: <searchLink fieldCode="DE" term="%22Finland%22">Finland</searchLink>
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  Data: In Finland, linear optimization has been used to search for sustainable national harvest levels for over 30 years—commonly maximizing net present value from forests county by county, while ensuring sustainability of wood production by requiring nondecreasing harvest levels over time. However, this approach does not help policymakers understand how the selected harvest level is reached and what affects the result. Moreover, optimizing per county may lead to an inefficient solution, as the counties serve as constraints. National-level interactive planning is a better approach, but such interactive optimization is compute-intensive. We present an interactive multiobjective optimization approach applying the NAUTILUS Navigator method. It is based on precalculated optimal solutions and gradual improvements from the nadir (the worst solution). We apply the approach in a novel way: starting with a sparse representation of optimal solutions and generating a denser representation in the area of interest, saving computational resources. The problem formulation is also improved during the solution process. Moreover, the interactive approach advises decision makers on the consequences of the selected solution better than a few preselected scenarios. The decision maker can direct the solution process and find preferred solutions. The results also show improvement in solutions when the county-level constraints are removed. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asx&AN=193632179
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1139/cjfr-2025-0277
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 13
        StartPage: 1
    Subjects:
      – SubjectFull: Finland
        Type: general
      – SubjectFull: Multi-objective optimization
        Type: general
      – SubjectFull: Linear programming
        Type: general
      – SubjectFull: Decision support systems
        Type: general
      – SubjectFull: Forest management
        Type: general
      – SubjectFull: Automated planning & scheduling
        Type: general
      – SubjectFull: Logging
        Type: general
    Titles:
      – TitleFull: Searching for sustainable national forest harvest levels through interactive multiobjective optimization.
        Type: main
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            NameFull: Saini, Bhupinder Singh
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            NameFull: Kangas, Annika
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            NameFull: Mehtätalo, Lauri
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            NameFull: Hirvelä, Hannu
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            NameFull: Shavazipour, Babooshka
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            NameFull: Miettinen, Kaisa
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          Dates:
            – D: 12
              M: 05
              Text: 5/12/2026
              Type: published
              Y: 2026
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              Value: 00455067
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              Value: 56
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            – TitleFull: Canadian Journal of Forest Research
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