Abstract
Tabu search is a simple, yet powerful meta-heuristic based on local search. This paper presents current taxonomy of parallel tabu search algorithms and compares three parallel TS algorithms based on Tabucol, an algorithm for graph coloring. The experiments were performed on two different high performance architectures: an Itanium-based cluster and a shared-memory Sun server. The results are based on graphs available from the DIMACS benchmark suite.
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© 2007 Springer-Verlag Berlin Heidelberg
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Dąbrowski, J. (2007). Parallelization Techniques for Tabu Search. In: Kågström, B., Elmroth, E., Dongarra, J., Waśniewski, J. (eds) Applied Parallel Computing. State of the Art in Scientific Computing. PARA 2006. Lecture Notes in Computer Science, vol 4699. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75755-9_130
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DOI: https://doi.org/10.1007/978-3-540-75755-9_130
Publisher Name: Springer, Berlin, Heidelberg
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