Select issue
Silva Fennica 1926-1997
1990-1997
1980-1989
1970-1979
1960-1969
1950-1959
1940-1949
1926-1939
Acta Forestalia Fennica
1992-1999
1984-1991
1974-1983
1968-1973
1953-1968
1933-1952
1913-1932
Articles containing the keyword 'habitat suitability index (HSI)'
Category : Research article
article id 396,
category
Research article
(2005).
Examining the performance of six heuristic optimisation techniques in different forest planning problems.
Silva Fennica
vol.
39
no.
1
article id 396.
https://doi.org/10.14214/sf.396
Keywords:
genetic algorithms;
simulated annealing;
ecological planning;
habitat suitability index (HSI);
Hero;
random search;
tabu search
Abstract |
View details
|
Full text in PDF |
Author Info
The existence of multiple decision-makers and goals, spatial and non-linear forest management objectives and the combinatorial nature of forest planning problems are reasons that support the use of heuristic optimisation algorithms in forest planning instead of the more traditional LP methods. A heuristic is a search algorithm that does not necessarily find the global optimum but it can produce relatively good solutions within reasonable time. The performance of different heuristics may vary depending on the complexity of the planning problem. This study tested six heuristic optimisation techniques in five different, increasingly difficult planning problems. The heuristics were evaluated with respect to the objective function value that the techniques were able to find, and the time they consumed in the optimisation process. The tested optimisation techniques were 1) random ascent (RA), 2) Hero sequential ascent technique (Hero), 3) simulated annealing (SA), 4) a hybrid of SA and Hero (SA+Hero), 5) tabu search (TS) and 6) genetic algorithm (GA). The results, calculated as averages of 100 repeated optimisations, were very similar for all heuristics with respect to the objective function value but the time consumption of the heuristics varied considerably. During the time the slowest techniques (SA or GA) required for convergence, the optimisation could have been repeated about 200 times with the fastest technique (Hero). The SA+Hero and SA techniques found the best solutions for non-spatial planning problems, while GA was the best in the most difficult problems. The results suggest that, especially in spatial planning problems, it is a benefit if the method performs more complicated moves than selecting one of the neighbouring solutions. It may also be beneficial to combine two or more heuristic techniques.
-
Pukkala,
University of Joensuu, Faculty of Forestry, P.O. BOX 111, FI-80101 Joensuu, Finland
E-mail:
timo.pukkala@forest.joensuu.fi
- Kurttila, Finnish Forest Research Institute, Joensuu Research Centre, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: mk@nn.fi
Click this link to register to Silva Fennica.
If you are a registered user, log in to save your selected articles for later access.
Your selected articles
Silva Fennica ·
Finnish Society of Forest Science
