Heuristic Optimization of Thinning Individual Douglas-Fir

Research Highlights: (1) Optimizing mid-rotation thinning increased modeled land expectation values by as much 5.1–10.1% over a representative reference prescription on plots planted at 2.7 and 3.7 m square spacings. (2) Eight heuristics, five of which were newly applied to selecting individual trees for thinning, produced prescriptions near identical quality. (3) Based heuristic sampling properties, we introduced variant the hero with 5.3–20% greater computational efficiency. Background Objectives: Thinning, is arguably most subjective human intervention in life stand, commonly executed limited decision support tree selection. This study evaluated heuristics’ ability selection factorial experiment that considered method, density, age, rotation length. Materials Methods: The Organon growth model was used financial optimization even age Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) harvest rotations consisting single followed clearcutting high-productivity site. We two versions heuristic, four Monte Carlo heuristics (simulated annealing, record-to-record travel, threshold accepting, great deluge), genetic algorithm, tabu search their efficiency maximizing value. Results: With 50–75 years 4% discount rate, always other methods. computationally efficient required 2.8–3.4 times more computation than hero. algorithm 4.2–8.4 21–52 times, respectively, Conclusions: accuracy resulting quality stand measurement, yield models linked rather choice heuristic. However, performance may be sensitive chosen models.