| Summary: | The problem bucking of trees into logs is solved using dynamic programming. The state of
the model is described by the physical dimensions of the tree, such as length, diameters and
sweep. This thesis incorporates decay as a description of the state.
This thesis begins with a detailed analysis of decay morphology, obtaining the expected
values and dispersion of key variables. The main goal of this thesis is to evaluate the decay
information that could be gathered; this is done by incorporating different levels of information
into the bucking algorithms. The first level assumes perfect information; in this case the algorithm
is provided with the observed diameter of decay and its actual length. The second level uses an
observed decay diameter and a length estimated based on the decay model. The third level also
uses the observed decay diameter, but now the length is assumed to be a random variable, whose
distribution parameters are based on the decay model. Furthermore, the models will be compared
to the normal practices of forestry companies of British Columbia. A test of four hundred trees in
four species, Spruce, Lodgepole Pine, Balsam Fir and Western Red Cedar was performed. Clear
improvements were found when bucking with algorithms that consider decay. The value increased
an average of 11.9%. One of the most relevant findings of this thesis is that this significant lift
does not result from lower stumpage and transportation costs, but from higher recoveries. The
stumpage and transportation costs are on average higher in the proposed algorithms as compared
to the normal practices. This means that the use of bucking algorithms that incorporate decay
translates into gains for the lumber companies as well as for the Provincial Government and the
transportation industry. === Business, Sauder School of === Graduate
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