With this course, we hope to provide students with the theory 
and tools to enable them to develop forest plans with spatial 
constraints, and to understand the advantages and limitations of 
the different techniques.  The specific outcomes for students 
are:

1. Learn the most common types of operations research techniques 
for used in practice and demonstrated in the literature, as 
related to forest and natural resource management planning.

2. Describe the vegetation and environment that might be present 
in the future under a variety of forest plan alternatives.

3. Collect, process, analyze, project, and present spatial and 
non-spatial data that are useful for decision-making and 
implementing forest plans across multiple scales.

4. Assess the reliability and validity of forest plans developed 
with the various planning techniques.

5. Develop key elements of the management decision and 
operations process, including: a) identify key management 
problems facing decision makers/ owners, b) identify management 
alternatives, c) assemble data and information to evaluate 
alternatives using state-of-the-art analytical methods, and d) 
identify trade-offs among decision options.

1. Forest planning and planning problem formulations
2. Spatial objectives and constraints
3. Linear programming
4. Integer programming
5. Monte Carlo simulation
6. Simulated Annealing
7. Threshold accepting
8. Great Deluge algorithm
9. Tabu search
10. Genetic algorithms
11. Evaluating the quality of forest planning results
12. Advanced forestry and wildlife planning problems
13. Term projects

You are expected to conduct yourself at all times in accordance 
with the University Academic Honesty Policy.  Violations of the 
policy will be vigorously pursued and prosecuted.  Please 
consult the policy guidebook "A Culture of Honesty:  Policies 
and Procedures on Academic Honesty" available in Room 1-203.