A tabu search algorithm for finding good forest harvest schedules satisfying green-up constraints

Due to environmental concerns, forest harvesting in many regions must now satisfy adjacency, or green-up constraints. As a result, the forest harvesting problem, which originally could be formulated as a linear programming problem, becomes combinatorial in nature. Moreover, current harvest scheduling codes, like FORPLAN, Timber RAM and others, are unable to generate harvest schedules satisfying the adjacency constraints. In this paper we formulate forest harvesting problems with adjacency constraints arising in the Tangier watershed as multicriteria optimization problems. We use tabu search to investigate the trade-offs among the different criteria which were chosen as the total volume of lumber cut, the period to period deviation from even-flow of lumber during a harvest rotation and adjacency violations. Apparently, the tabu search methodology can be easily applied to solve harvesting problems with adjacency constraints. For harvesting problems in the Tangier watershed, the tabu search is shown to produce better schedules than the O'Hara et al. method (1989), which is considered to be one of the most effective approaches for forest harvesting problems. We also confirm the expected outcome that requiring adherence to green-up constrains, or to certain limitations on flow deviations, will reduce the total volume of lumber that can be cut. However, our approach is sufficiently effective to reveal that for the forest harvesting problems in the Tangier watershed which we studied, this volume reduction does not exceed 8%, and sometimes even does not exceed 2% of the total volume that could be possibly cut.