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Forest Harvest Scheduling with Endogenous Road Costs

Kai Ross et al.

INFORMS Journal on Applied Analytics2018https://doi.org/10.1287/inte.2017.0926article
AJG 2ABDC B
Weight
0.47

Abstract

The Washington State Department of Natural Resources (DNR) manages over 800,000 hectares of forested state trust lands and 20,000 kilometers of forest roads in Washington State. Forest harvest and road reconstruction decisions greatly impact the agency’s cash flows and its ability to meet its fiduciary obligations. We introduce a mixed-integer programming model that integrates harvest and road scheduling decisions. We show how DNR embedded the new model in its workflows and applied it to the Upper Clearwater River Landscape in the Olympic Experimental State Forest. We find that the forest valuation of the Upper Clearwater increased by $0.5–$1 million (0.4–1.1 percent) because of the new method, which allowed the DNR to concentrate capital expenditures in support of harvest and road operations in both time and space. This led to a 14.5 percent reduction in the size of the active road network. DNR is now in the process of scaling the new approach to the entire forest estate.

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https://doi.org/https://doi.org/10.1287/inte.2017.0926

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@article{kai2018,
  title        = {{Forest Harvest Scheduling with Endogenous Road Costs}},
  author       = {Kai Ross et al.},
  journal      = {INFORMS Journal on Applied Analytics},
  year         = {2018},
  doi          = {https://doi.org/https://doi.org/10.1287/inte.2017.0926},
}

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Evidence weight

0.47

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.32 × 0.4 = 0.13
M · momentum0.75 × 0.15 = 0.11
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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