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Parallel Ant Colony Optimization for the Quadratic Assignment Problems with Symmetric Multi Processing

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5217))

Abstract

Recently symmetric multi processing (SMP) has become available at a reasonable cost. In this paper, we propose several types of parallel ACO algorithms with SMP for solving the quadratic assignment problem (QAP). These models include the master-slave models and the island models. We evaluated each parallel algorithm with a condition that the run time for each parallel algorithm and the base sequential algorithm are the same. The results suggest that using the master-slave model with increased iteration of ACO algorithms is promising in solving QAPs.

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Marco Dorigo Mauro Birattari Christian Blum Maurice Clerc Thomas Stützle Alan F. T. Winfield

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© 2008 Springer-Verlag Berlin Heidelberg

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Tsutsui, S. (2008). Parallel Ant Colony Optimization for the Quadratic Assignment Problems with Symmetric Multi Processing. In: Dorigo, M., Birattari, M., Blum, C., Clerc, M., Stützle, T., Winfield, A.F.T. (eds) Ant Colony Optimization and Swarm Intelligence. ANTS 2008. Lecture Notes in Computer Science, vol 5217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87527-7_38

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  • DOI: https://doi.org/10.1007/978-3-540-87527-7_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87526-0

  • Online ISBN: 978-3-540-87527-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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