A Study of Breakout Local Search for the Minimum Sum Coloring Problem
Given an undirected graph G = (V,E), the minimum sum coloring problem (MSCP) is to find a legal assignment of colors (represented by natural numbers) to each vertex of G such that the total sum of the colors assigned to the vertices is minimized. In this paper, we present Breakout Local Search (BLS) for MSCP which combines some essential features of several well-established metaheuristics. BLS explores the search space by a joint use of local search and adaptive perturbation strategies. Tested on 27 commonly used benchmark instances, our algorithm shows competitive performance with respect to recently proposed heuristics and is able to find new record-breaking results for 4 instances.
Keywordsminimum sum coloring adaptive perturbation strategy heuristic combinatorial optimization
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- 1.Battiti, R., Protasi, M.: Reactive search, a history-based heuristic for max-sat. ACM Journal of Experimental Algorithmics 2 (1996)Google Scholar
- 2.Benlic, U., Hao, J.K.: Breakout local search for maximum clique problems. Operations Research 40(1), 192–206 (2013)Google Scholar
- 6.Helmar, A., Chiarandini, M.: A local search heuristic for chromatic sum. In: MIC 2011, pp. 161–170 (2011)Google Scholar
- 10.Li, Y., Lucet, C., Moukrim, A., Sghiouer, K.: Greedy algorithms for minimum sum coloring algorithm. In: Proceedings of LT 2009 (2009)Google Scholar
- 11.Lourenco, H.R., Martin, O., Stützle, T.: Iterated local search. Handbook of Meta-heuristics. Springer, Heidelberg (2003)Google Scholar
- 12.Malafiejski, M.: Sum coloring of graphs. In: Kubale, M. (ed.) AMS Graph Colorings, pp. 55–65 (2004)Google Scholar