Figure 1. First period harvest units on the Putnam Tract using mixed integer programming methods.

Figure 2. First period harvest units on the Putnam Tract using integer programming methods.

Figure 3. First period harvest units on the Putnam Tract using goal programming methods.

Figure 4. First period harvest units on the Putnam Tract using binary search methods.

Figure 5. A generic Monte Carlo simulation process. Randomly develop a forest plan Calculate the objective function value Best plan? Save the plan as the best plan Develop more plans? Report best forest plan Yes NoYes No

Figure 6. A generic simulated annealing process. Randomly change a stand and a harvest timing Calculate the resulting objective function value Best plan? Save the plan as the best plan Try other changes ? Report best forest plan Yes No Yes No Pass test? Save the plan as the current forest plan Revert to previous forest plan Change temp., check simulated annealing criteria Yes No

Figure 7. A generic tabu search process. Best plan? Save the plan as the best plan Try other changes ? Report best forest plan Yes No Yes Tabu? Save the plan as the current forest plan Assess contribution of all choices Select the best choice Adjust tabu states Best plan? Yes No Yes

Figure 8. A general genetic algorithm search process. Save the plan as the best plan Try other changes ? Report best forest plan No Yes Develop population of forest plans Select two forest plans Replace other plans with these plans in the population Created best plan? Yes Create two new forest plans Apply mutations to the two new forest plans