Searching for prescriptive treatment schedules with a genetic algorithm a tool for forest management /
Abstract (Summary)
This thesis describes research on the use of a genetic algorithm (GA) to prescribe
treatment plans for forest management at the stand level. Forest management refers to making
decisions about when and where to intervene in the natural growth of forests to achieve
objectives, such as enhancing the visual quality of a stand or maximizing timber yield. A
prescription is a schedule of thinning treatments applied to stands over a planning horizon.
When multiple management goals exist treatment prescription becomes a complex multiobjective
problem. The effectiveness of a GA depends on selecting an appropriate representation
and germane fitness function. These design decisions are reviewed, followed by a series of
experiments testing the performance of the GA. Different parameter settings are compared and
the GA is contrasted with some other heuristic search methods. The final experiment compares a
plan created by the GA to a plan recommended by a human expert.
Bibliographical Information:
Advisor:
School:The University of Georgia
School Location:USA - Georgia
Source Type:Master's Thesis
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