Resumen de Heuristics for the Robust Coloring Problem

Miguel Ángel Gutiérrez Andrade, Pedro Lara Velázquez, Rafael López Bracho, Javier Ramirez Rodríguez

• español

  Sean y dos grafos complementarios. Dada una función de penalización en las aristas de , la rigidez de una -coloración de(Error rendering LaTeX formula)(Error rendering LaTeX formula)k$-coloración de rigidez mínima. Este trabajo realiza un estudio comparativo de varias técnicas heurísticas: Recocido Simulado, GRASP, y Búsqueda Dispersa. Los resultados aquí presentados son los mejores obtenidos para el PCR.

• English

  Let $G$ and $\bar{G}$ be complementary graphs. Given a penalty function defined on the edges of $G$, we will say that the rigidity of a $k$-coloring of $G$ is the sum of the penalties of the edges of G joining vertices of the same color. Based on the previous definition, the Robust Coloring Problem (RCP) is stated as the search of the minimum rigidity $k$-coloring. In this work a comparison of heuristics based on simulated annealing, GRASP and scatter search is presented. These are the best results for the RCP that have been obtained.