The degree-constrained minimum spanning tree problem, which involves finding a minimum spanning tree of a given graph with upper bounds on the vertex degrees, has found multiple applications in several domains. In this paper, we propose a novel CP approach to tackle this problem where we extend a recent branch-and-bound approach with an adaptation of the LKH local search heuristic to deal with trees instead of tours. Every time a solution is found, it is locally optimised by our new heuristic, thus yielding a tightened cut. Our experimental evaluation shows that this significantly speeds up the branch-and-bound search and hence closes the performance gap to the state-of-the-art bottom-up CP approach.
CITATION STYLE
Thiessen, M., Quesada, L., & Brown, K. N. (2020). Improving a Branch-and-Bound Approach for the Degree-Constrained Minimum Spanning Tree Problem with LKH. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12296 LNCS, pp. 447–456). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-58942-4_29
Mendeley helps you to discover research relevant for your work.