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A holistic optimization framework for forest machine trail network design accounting for multiple objectives and machines
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Sveriges lantbruksuniversitet, Swedish University of Agricultural Sciences.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. (Design Optimization)
2019 (Engelska)Ingår i: Canadian Journal of Forest Research, ISSN 0045-5067, E-ISSN 1208-6037, Vol. 49, nr 2, s. 111-120Artikel i tidskrift (Refereegranskat) 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.

Ort, förlag, år, upplaga, sidor
2019. Vol. 49, nr 2, s. 111-120
Nationell ämneskategori
Annan matematik Skogsvetenskap
Identifikatorer
URN: urn:nbn:se:umu:diva-154287DOI: 10.1139/cjfr-2018-0258ISI: 000458033400001OAI: oai:DiVA.org:umu-154287DiVA, id: diva2:1270962
Tillgänglig från: 2018-12-14 Skapad: 2018-12-14 Senast uppdaterad: 2019-02-20Bibliografiskt granskad

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Hosseini, AhmadWadbro, Eddie

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Canadian Journal of Forest Research
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