Speaker
Description
Value-based bucking is a central optimisation task in cut-to-length harvesting systems, where stem segmentation into assortments determines both product distributions and economic performance.
In Norway, harvester price matrices are typically harmonised within procurement regions, even though considerable variation exists in stem form, internal wood quality, and other tree-level characteristics that influence product value realisation. This study examines how tree-level quality attributes affect optimal bucking decisions and how these shifts propagate along the supply chain under Norwegian operational conditions. Using detailed harvester recorded stem measurements (.hpr) combined with a dynamic programming bucking simulator (OptBuck), we simulated assortment outcomes across multiple scenarios that incorporate variation in wood properties.
Results show that including quality related attributes in bucking optimisation systematically alters assortment composition and net stem value, with pronounced impacts on the proportion and value of sawlogs, being the most economically significant assortment. These changes further influence downstream logistics flows and overall supply chain economics. The findings emphasise the need to integrate tree-level quality information into bucking parameterisation and procurement planning to enhance value capture and operational efficiency in modern forestry.
| Keywords | "Tree-bucking; Wood properties; OptBuck" |
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