An effective modeling and solution approach for the generalized independent set problem

The generalized independent set (GIS) problem was first introduced by Hochbaum and Pathria (Forest Sci 43(4), 544–554, 1997) and independently explored in greater detail by Hochbaum (Manage Sci 50(6), 709–123, 2004). This problem, with applications in forest management and a variety of related areas, is a generalization of the classical maximum independent set problem. In this paper we highlight a natural, nonlinear formulation for the problem that is an attractive alternative to the linear model found in the literature. The effectiveness of this alternative formulation is demonstrated by computational experience on test problems of varying size and density, disclosing a dramatic reduction in the time to obtain optimal and near optimal solutions and an ability to solve much larger problems.