An ant colony system approach for solving the at-least version of the generalized minimum spanning tree problem

We consider the "at least" version of the generalized minimum spanning tree problem (L-GMST). Unlike the MST, the L-GMST is known to be NP-hard. In this paper, we propose an ant colony system based solution approach for the L-GMST. A key feature of our algorithm is its use of ants of different behavioral characteristics, which are adapted over time. Computational results on datasets used in earlier literature indicate that our algorithm provides similar or better results for most of them.