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

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Title: Searching for sustainable national forest harvest levels through interactive multiobjective optimization.
Authors: Saini, Bhupinder Singh1 (AUTHOR) bhupinder.s.saini@jyu.fi, Kangas, Annika2 (AUTHOR), Mehtätalo, Lauri2 (AUTHOR), Hirvelä, Hannu3 (AUTHOR), Shavazipour, Babooshka1 (AUTHOR), Miettinen, Kaisa4 (AUTHOR)
Source: Canadian Journal of Forest Research. 5/12/2026, Vol. 56, p1-13. 13p.
Subject Terms: *Forest management, *Logging, Multi-objective optimization, Linear programming, Decision support systems, Automated planning & scheduling
Geographic Terms: Finland
Abstract: 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]
Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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An: 193632179
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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="%22Forest+management%22">Forest management</searchLink><br />*<searchLink fieldCode="DE" term="%22Logging%22">Logging</searchLink><br /><searchLink fieldCode="DE" term="%22Multi-objective+optimization%22">Multi-objective optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Linear+programming%22">Linear programming</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+support+systems%22">Decision support systems</searchLink><br /><searchLink fieldCode="DE" term="%22Automated+planning+%26+scheduling%22">Automated planning & scheduling</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]
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  Data: <i>Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1139/cjfr-2025-0277
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      – Code: eng
        Text: English
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        PageCount: 13
        StartPage: 1
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      – SubjectFull: Forest management
        Type: general
      – SubjectFull: Logging
        Type: general
      – SubjectFull: Multi-objective optimization
        Type: general
      – SubjectFull: Linear programming
        Type: general
      – SubjectFull: Decision support systems
        Type: general
      – SubjectFull: Automated planning & scheduling
        Type: general
      – SubjectFull: Finland
        Type: general
    Titles:
      – TitleFull: Searching for sustainable national forest harvest levels through interactive multiobjective optimization.
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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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            – 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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