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Parallel Tabu Search for Large Optimization Problems

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Meta-Heuristics

Abstract

This paper presents a parallel implementation of a tabu search algorithm based on adaptive parallelism. Adaptive parallelism demonstrates that massively parallel computing using a hundred of heterogeneous machines is feasible to solve large optimization problems. The parallel tabu search algorithm includes different tabu list sizes and new intensification/diversification mechanisms. Encouraging results have been obtained in solving the quadratic assignment problem. We have improved the best known solutions for some large real-world problems.

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Talbi, EG., Hafidi, Z., Geib, JM. (1999). Parallel Tabu Search for Large Optimization Problems. In: Voß, S., Martello, S., Osman, I.H., Roucairol, C. (eds) Meta-Heuristics. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5775-3_24

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  • DOI: https://doi.org/10.1007/978-1-4615-5775-3_24

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-7646-0

  • Online ISBN: 978-1-4615-5775-3

  • eBook Packages: Springer Book Archive

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