Forest landscape management modeling using simulated annealing

This paper presents a new landscape management model using a simulated annealing approach. The model is capable of achieving target landscape structure, in the form of composition and configuration objectives, in a near optimal fashion by spatially and temporally scheduling treatment interventions. Management objectives and constraints are identified in an objective function. Penalty cost functions for each objective establish common non-monetary units, and a mechanism for making trade-offs among different objectives. Management strategies, as well as alternative solutions as combinations of treatment scheduling of each stand, are formulated around treatment regimes, including varying intensities of planting, precommercial thinning, commercial thinning, two-stage harvesting and clear-cutting. The model then examines alternative solutions using a heuristic process, and evaluates their effects on the objective over an entire planning horizon. The model was tested on a 20,000 ha (987 stands) hypothetical forest landscape with four replicates, differing in initial age class composition and spatial configuration. Management objectives included: (i) maximizing harvest volume, (ii) minimizing deviations in harvest flow, (iii) maintaining harvest block size between 40 and 100 ha, (iv) maintaining a one period adjacency delay, and (v) achieving an inverse-J distribution of harvest opening patches. Objective accomplishment, when compared to an aspatial optimal solution, varied from 72% for even flow harvest, to 99.9% for adjacency delay. These results generally reflect the objective priorities established for the test. Results also suggested that the achievement of an inverse-J distribution of harvest opening patches depended not only upon the spatial harvest pattern, but initial forest conditions as well. In the case of the test forests, however, the effects of different initial age class structure and spatial configuration lasted a relatively short time. We conclude that simulated annealing allows a great deal of flexibility in designing landscape management in a near optimal fashion. (C) 2002 Elsevier Science B.V. All rights reserved.