journal article Nov 06, 2020

A heuristic for the convex recoloring problem in graphs

View at Publisher Save 10.1111/itor.12896
Abstract
AbstractWe consider a coloring as a function that assigns a color to a vertex, regardless of the color of its neighbors. In this sense, a coloring is said to be convex if every set of all same colored vertices induces a connected subgraph. The Convex Recoloring Problem finds the minimum number of recolored vertices needed to turn a coloring convex. This problem is most commonly studied considering trees due to its origins in Computational Biology, but in this paper, we focus on general graphs. We propose a heuristic based on the Greedy Randomized Adaptive Search Procedure to solve the problem. We present computational experiments for our heuristic and compare it to an Integer Linear Programming (ILP) model from the literature. In these experiments, our heuristic recolored at most one vertex more than the ILP model, and it was also able to give better solutions when the ILP model was unable to find the optimal solution within the time limit. We also introduce a set of benchmark instances for the problem.
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References
19
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Greedy Randomized Adaptive Search Procedures

Thomas A. Feo, Mauricio G. C. Resende

Journal of Global Optimization 10.1007/bf01096763
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Metrics
1
Citations
19
References
Details
Published
Nov 06, 2020
Vol/Issue
29(3)
Pages
1454-1478
License
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Funding
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Award: 001
Conselho Nacional de Desenvolvimento Cientifico e Tecnologico Award: 304380/2018‐0
Fundação de Amparo a Pesquisa do Estado de São Paulo Award: 2015/11937‐9
Cite This Article
Ana Paula S. Dantas, Cid C. de Souza, Zanoni Dias (2020). A heuristic for the convex recoloring problem in graphs. International Transactions in Operational Research, 29(3), 1454-1478. https://doi.org/10.1111/itor.12896
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