Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS) — ##plugins.generic.mcfnsReadingTools.readingTools##

Optimal parameter settings to improve the efficiency of solving harvest scheduling models with adjacency constraints were examined using Ilog’s Cplex® 11.2 optimizer tuning tool.  A total of 160 randomly generated hypothetical forests were created with either 50 or 100 stands and four age-class distributions.  Mixed integer programming problems were formulated in Model I form with four different adjacency constraint types, two Unit Restriction Model (URM) adjacency constraints (Pairwise and Maximal Clique) and two Area Restriction Model (ARM) formulations (Path and Generalized Management Unit).  A total of 640 problem sets-where a set is a common forest size, age-class distribution, and adjacency constraint type-were tuned to determine optimal parameter settings and then were solved at both the default and optimal settings.  In general, mean solution time was less for a given problem set using the optimal parameters compared to the default parameters.  The results discussed provide a simple approach to decrease the solution time of solving mixed integer forest planning problems with adjacency constraints.