Comparative analysis of algorithms to generate adjacency constraints

A mathematical programming formulation of the area-based forest planning problem can result in a large number of adjacency constraints with much potential for redundancy. Two heuristic algorithms have been proposed for reducing redundant adjacency constraints generated by the conventional algorithm. In this paper another analytical algorithm is proposed, and its efficiency and that of the conventional algorithm and the two heuristics are evaluated and compared. Comparison is based on the number of constraints, and on the computational effort needed both to derive the adjacency constraints and to solve the associated planning problem. Evaluation for several adjacency maps shows that the conventional algorithm has the largest number of constraints, with a low degree of effort in derivation of adjacency constraints and a small computational task to find a final solution. The first heuristic algorithm has the smallest number of constraints but involves a high degree of effort and a large computational task. The second heuristic has a small number of constraints with a moderate degree of effort and a large computational task, and the proposed algorithm has a small number of constraints with a low degree of effort and a moderate to large computational task.