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Spatial restrictions of harvesting have been extensively studied due to a number of environmental, social and legal regulations. Many spatial restrictions are defined by adjacency constraints, for which a number of algorithms have been developed. Research into the unit restriction model (URM) using a branch and bound algorithm focused on decreasing the number of adjacency constraints in harvest scheduling models, since the early solvers have been limited by the number of constraints and integer decision variables. However, this approach can lead to a loss of efficiency in solving mixed integer models. Recent improvements in commercial solvers and personal computers have made the reduction of constraints less relevant, since many solvers now accept an unlimited number of constraints and decision variables. The aim of this paper was to compare the time efficiency of solving unit restriction harvest scheduling models with different types of adjacency constraints using a commercial solver. The presented results indicate that the type of adjacency constraints can have a significant effect on the solving time and therefore could be a crucial factor of the time required for developing forest plans. We note that pairwise adjacency constraints may be sufficient today for addressing unit restriction forest harvest scheduling problems

Time Efficiency of Selected Types of Adjacency Constraints in Solving Unit Restriction Models