A column generation approach for solving a non-temporal forest harvest model with spatial structure constraints

We present an integer programming model for a non-temporal forest harvest problem with constraints on a clearcut size and on the total area of old growth patches with a minimum size requirement. The model has a very large number of variables for operationally sized problems which precludes the use of exact solution methods. We propose column generation to solve the linear relaxation of the model and a linear programming rounding heuristic to obtain a solution to the model. Column generation may not solve exactly the linear relaxation because the optimization problems associated with the pricing subproblems are NP-hard. We present heuristics for these subproblems. Computational results for test instances and for a real life instance that corresponds to a large Portuguese forest are reported.