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Ant Colony Optimization in Hadoop Ecosystem

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Book cover Multimedia and Network Information Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 506))

Abstract

Paper focuses on bringing the classic ACO (Ant Colony Optimization) for TSP (Travelling Salesman Problem) to Hadoop ecosystem. Classic ACO can be parallelized for efficiency. Especially today, with virtualization and cloud computing it is particularly easy to run ACO simulation on many nodes. However the distribution part adds an extra cost to an implementation of a simulation.

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Notes

  1. 1.

    https://d3js.org/.

  2. 2.

    https://github.com/google/gson.

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Author information

Authors and Affiliations

  1. Wrocław University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland

    Marek Kopel

Authors
  1. Marek Kopel
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Correspondence to Marek Kopel .

Editor information

Editors and Affiliations

  1. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wroclaw, Poland

    Aleksander Zgrzywa

  2. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Kazimierz Choroś

  3. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Andrzej Siemiński

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Kopel, M. (2017). Ant Colony Optimization in Hadoop Ecosystem. In: Zgrzywa, A., Choroś, K., Siemiński, A. (eds) Multimedia and Network Information Systems. Advances in Intelligent Systems and Computing, vol 506. Springer, Cham. https://doi.org/10.1007/978-3-319-43982-2_17

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  • DOI: https://doi.org/10.1007/978-3-319-43982-2_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43981-5

  • Online ISBN: 978-3-319-43982-2

  • eBook Packages: EngineeringEngineering (R0)

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