Abstract
In this paper, we propose a new neighborhood structure based on the improvement graph for solving the Robust Graph Coloring Problem, an interesting extension of classical graph coloring. Different from the traditional neighborhood where the color of only one vertex is modified, the new neighborhood involves several vertices. In addition, the questions of how to select the modified vertices and how to modify them are modelled by an improvement graph and solved by a Dynamic Programming method. The experimental results clearly show that our new improvement graph based k-exchange cycle neighborhood improves the accuracy significantly, especially for large scale heuristic search.
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Guo, S., Kong, Y., Lim, A., Wang, F. (2004). A New Neighborhood Based on Improvement Graph for Robust Graph Coloring Problem. In: Webb, G.I., Yu, X. (eds) AI 2004: Advances in Artificial Intelligence. AI 2004. Lecture Notes in Computer Science(), vol 3339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30549-1_55
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DOI: https://doi.org/10.1007/978-3-540-30549-1_55
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