A Comparison of Numerical Method for Optimizing Even Aged Stand Management

1990

S. 961-969

4 Abb., 8 Tab., 20 Lit. Ang.

Unselbständiges Werk

200088843

A two-species, whole-stand, deterministic growth model was combined with three optimization methods to derive management regimes for species composition, thinnings, and rotation age, with the objective of maximizing soil expectation value. The methods compared were discrete time - discrete state dynamic programming, direct search using the Hooke and Jeeves algorithm, and random research. Optimum solutions for each of the methods varied considerably, required unequal amount of computational time, and were not equally stable. Dynamic programming located global optimal solutions but did not determine them accurately, owing the discretized state space. Direct search yielded the largest objective function values with comparable computational effort, although the likelihood of finding a global optimum solution was high only for smaller problems with up to two or three thinnings during the rotation. Random search solutions varied considerably with regard to growing stock level and species compositon and did not define a consistent management guideline. In general, direct search and dynamic programming appeared to be superior to random search.