Heuristic Optimization

“A heuristic is a technique which seeks good (i.e. near-optimal) solutions at a reasonable computational cost without being able to guarantee either feasibility or optimality, or even in many cases to state how close to optimality a particular feasible solution is” (Reeves 1993). In the context of forest planning, the used heuristic techniques iteratively search for optimal combination of treatments for compartments. Thus, the treatments of compartments are the actual decision variables in the search process and the quality of the solution is usually measured by the value of the planning area level objective function.

Forest planning problems often have an integer nature, i.e. the compartments should not be split into parts. In addition, management activities in certain compartment may influence adjacent compartments through, e.g., increased wind damage or drainage risks. In addition, too large open areas certainly change the far-view scenery. These are reasons for adding spatial constraints upon harvesting activities of adjacent compartments to forest planning problems (Brumelle et al. 1997; Tarp and Helles 1997; Baskent and Keles 2005). These kinds of problems are called dispersion problems (Ö hman 2002). On the other hand, clustering of certain types of compartments has been found beneficial from the viewpoint of species viabilities (e.g. Harrison and Fahrig 1995; Kurttila 2001; Ö hman 2002; Nalle et al. 2004). In addition, sometimes it is beneficial to cluster harvesting areas, at least when the size of the compartments is small (Lu and Eriksson 2000; Heinonen et al. 2007). These clustering problems that prevent fragmentation of, e.g., old forest have become more common during the last decade. In forest planning, the above described planning problems where the solution is a set of integers are hard, even impossible, to solve using mathematical programming based techniques. Instead, heuristic techniques can solve these kinds of problems (see Kurttila 2001; Borges et al. 2002; Baskent and Keles 2005 for reviews on the use of spatial objectives and heuristic techniques in forest planning). The integer nature of planning problems and the use of spatial objectives are the most important reasons for the increased popularity of heuristics in forest planning.