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A holistic optimization framework for forest machine trail network design accounting for multiple objectives and machines
Umeå University, Faculty of Science and Technology, Department of Computing Science.
Sveriges lantbruksuniversitet, Swedish University of Agricultural Sciences.
Umeå University, Faculty of Science and Technology, Department of Computing Science. (Design Optimization)
2019 (English)In: Canadian Journal of Forest Research, ISSN 0045-5067, E-ISSN 1208-6037, Vol. 49, no 2, p. 111-120Article in journal (Refereed) Published
Abstract [en]

Ground-based mechanized forestry requires the traversal of terrain by heavy machines. The routes they take are often called machine trails, and are created by removing trees from the trail and placing the logs outside it. Designing an optimal machine trail network is a complex locational problem that requires understanding how forestry machines can operate on the terrain as well as the trade-offs between various economic and ecological aspects. Machine trail designs are currently created manually based on intuitive decisions about the importance, correlations, and effects of many potentially conflicting aspects. Badly designed machine trail networks could result in costly operations and adverse environmental impacts. Therefore, this study was conducted to develop a holistic optimization framework for machine trail network design. Key economic and ecological objectives involved in designing machine trail networks for mechanized cut-to-length operations are presented, along with strategies for simultaneously addressing multiple objectives while accounting for the physical capabilities of forestry machines, the impact of slope, and operating costs. Ways of quantitatively formulating and combining these different aspects are demonstrated, together with examples showing how the optimal network design changes in response to various inputs.

Place, publisher, year, edition, pages
2019. Vol. 49, no 2, p. 111-120
National Category
Other Mathematics Forest Science
Identifiers
URN: urn:nbn:se:umu:diva-154287DOI: 10.1139/cjfr-2018-0258ISI: 000458033400001OAI: oai:DiVA.org:umu-154287DiVA, id: diva2:1270962
Available from: 2018-12-14 Created: 2018-12-14 Last updated: 2019-02-20Bibliographically approved

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Hosseini, AhmadWadbro, Eddie

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CiteExportLink to record
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  • apa
  • ieee
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  • Other style
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf