The long-term planning of sustainable forest treatment at the landscape lev
el is an increasingly more complex task. Local treatment schedules, pertain
ing to homogeneous sub-areas called stands, must be developed over a time h
orizon of a few centuries. Thousands of local schedules must be coordinated
to satisfy hard constraints, and balance soft constraints and optimization
criteria. Constraints and objectives are defined in terms of economical, r
ecreational, and environmental effect.
The aim of the forest treatment schedule is twofold. Over the near time hor
izon, it must provide clear instructions for forest treatment. In addition,
sustainability over the full horizon must be demonstrated. In this context
, sustainability means balancing growth and yield in the long term, the pre
servation of bio-diversity, and catering for human recreational and cultura
l value. Conventional OR based approaches have failed to give satisfactory
results for this type of problem. We describe a method built on explicit co
nstraint descriptions and a memory-based local search procedure for solving
rich models of the long-term forest treatment scheduling problem. We also
describe a configurable decision support system, called Ecoplan, where the
scheduling kernel is based on our method.
The system relies heavily on close interaction with a stand simulator, whic
h must provide forestry knowledge necessary to guide the scheduling process
, including the definition of abstract forest treatment actions. Ecoplan al
so provides facilities for user interaction in the planning process, functi
onality for locking specific parts of a plan, and flexibility to alter key
factors in the plan such as active constraints and objective criteria. Tn t
his way, the system supports the definition and exploration of "what-if" sc
enarios.
The Ecoplan system has been built on the initiative of the major Norwegian
forest owners, addressing a problem area that is becoming increasingly more
complex to handle and more critical to society.