期刊
FOREST SCIENCE
卷 68, 期 2, 页码 193-199出版社
OXFORD UNIV PRESS INC
DOI: 10.1093/forsci/fxac005
关键词
log grading; wood procurement; logging; decision support; operations research; linear programming
类别
This study quantifies the potential value of log sorting through scenario-based analysis and proposes an optimization model to allocate logs to the most profitable mills. The results show that log sorting can increase profit in certain locations, but may not be profitable in other areas. The proposed method can help foresters and landowners increase the value of harvested timber and provide guidance on maximizing profit.
It is generally understood that sorting logs based on grade generates maximum value for all stakeholders. However, the benefits of sorting logs may depend on the location of a timber sale and distances to manufacturing mills. The objective is to quantify the potential value of log sorting through scenario-based analysis in different areas with divergent forest and mill types. An optimization model was developed to allocate logs from the timber sale to the highest profit-yielding mills. Factors considered by the model included logging and transportation cost, timber sale tract-to-mill distances, mills' acceptance criteria, and price at the mill gate. Four timber sales from across Wisconsin were selected for the study. Three scenarios were tested, with each scenario yielding different proportions of log sorts. The results showed that log sorting increased profit by up to $41.10 per cord in certain locations but was not profitable in other locations. Study Implications The methods proposed in this study can help foresters and landowners increase the value of harvested timber. Practitioners can use the proposed method to systematically assess the gain or loss in profit associated with log sorting at each timber sale. It also provides directives on the best mill for each log sort to be sent. The proposed method should be adopted to minimize underutilization of timber, especially in areas where profits are marginal.
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