MELA program consists of two parts: (1) an automated stand simulator based on individual trees
and (2) the optimization package based on linear programming, JLP (Lappi 1992).
MELA simulates automatically a finite number of alternative management schedules for
the management units according to the given simulation instructions.
Management schedules differ, for example, in timing or in magnitude of activities.
LP is applied to select among the simulated management schedules both an optimal
production programme for the whole forest area and corresponding management schedules for
the individual management units according to the goals and restrictions defined by the user.
Simulation of schedules for management units
The simulation of the management schedules for each management unit consists of states and events.
The events are natural processes (ingrowth, growth and mortality of trees) and
management activities (e.g. cuttings, silvicultural treatments, drainage of peatland,
fertilization, and changes in land use) simulated by the built-in basic event routines of
the MELA simulator. A set of models describing natural processes, human activities (or treatments),
timber prices, costs, management instructions etc. are utilized.
For example the growth of the trees is predicted by using stem diameter and
height increment distance independent tree level models.
Increment of diameter is a function of tree species, diameter and height of the tree,
basal area of the stand, site type, geographical location, etc.
(Hynynen et al. 2002, Ojansuu et al. 1991). Volume and timber assortments are obtained from
stem curve models as a function of tree species, diameter and height (Laasasenaho 1982).
The value of the stems is calculated from timber assortments and unit prices.
Respectively, the costs of logging and silviculture are calculated from unit prices and
time expenditure models (e.g. Kuitto et al. 1994, Rummukainen et al. 1995, Laitila et al. 2004,
Kärhä et al. 2004).
Integrated selection of forest and stand level management programme
JLP (Lappi 1992) linear programming optimization package is applied to select
simultaneously forest (production program) and management unit level (management proposal) solutions.
JLP is used because of its computing capacity, flexibility for the system integration and
additional analysis tools offered besides the LP algorithm.
"Built-in" constraints of JLP, for example area constraints and domains,
reduce the memory needs of actual LP problems compared with general LP packages.
The optimization problem is open, i.e. any of the stored decision variables (hundreds in total) and
their linear combinations are available as for decision criteria (objective or constraints) both for
the whole forestry unit and for the domains (any combinations of stands, overlapping if required,
defined by the JLP c-variables of the management units).
The decision variables describe the state and the development of forests, as well as forest production and
its economy and efficiency.
The role of methods, assumptions, models and data
Relevant forest resource data together with forest development, management and
economy models are required to accomplish any analyses.
When interpreting the results one should make the difference between
the general simulation-optimization principle applied in MELA and the actual data and
models used in the analyses.
Forest data and models have a great influence on the planning results and their relevance.
The methods are based on the general assumption that the natural processes and
thus the development of forest can be predicted, and
that the limited number of management schedules describes the future potentials of
forests with sufficient accuracy and relevance.
Only the expected values of the models are used in the simulation,
i.e. the stochastic variation in natural processes,
for example in the growth of the trees, has not been taken into account.
See MELA and JLP manuals for further information.