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Title: Solving the minimum labelling spanning tree problem using hybrid local search
Authors: Consoli, S
Darby-Dowman, K
Mladenović, N
Moreno-Perez, J A
Keywords: Combinatorial optimization
Graphs and Networks
Local search
Minimum labelling spanning trees
Publication Date: 2007
Series/Report no.: TR/02/07
Abstract: Given a connected, undirected graph whose edges are labelled (or coloured), the minimum labelling spanning tree (MLST) problem seeks a spanning tree whose edges have the smallest number of distinct labels (or colours). In recent work, the MLST problem has been shown to be NP-hard and some effective heuristics (Modified Genetic Algorithm (MGA) and Pilot Method (PILOT)) have been proposed and analyzed. A hybrid local search method, that we call Group-Swap Variable Neighbourhood Search (GS-VNS), is proposed in this paper. It is obtained by combining two classic metaheuristics: Variable Neighbourhood Search (VNS) and Simulated Annealing (SA). Computational experiments show that GS-VNS outperforms MGA and PILOT. Furthermore, a comparison with the results provided by an exact approach shows that we may quickly obtain optimal or near-optimal solutions with the proposed heuristic.
Appears in Collections:Mathematical Science
Dept of Mathematics Research Papers

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