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Visual Analytics Solution for Scheduling Processing Phases

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Intelligent Computing & Optimization (ICO 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 866))

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Abstract

University Examination Timetabling Problem (UETP) is a computationally complex scheduling problem. Visual Analytics (VA) is a modern visualization supported with automated processing method. The major impulse of the method lies in its ability to integrate the key component of scientific visualization and search based heuristics in the same optimization model. This paper presents a visual analytics process (VAP) adapted for UETP. The adaption involves the human context of visual analytics on timetabling data, which are typically processed computationally with local search algorithm and then visualized and interpreted by the user in order to perform problem solving with direct interactions between the primary data, processing and visualization. The three processing phases are invoked with user-driven and algorithmic-driven steering that analyses the combined effect with automatic tuning of algorithmic parameters based on constraints and the criticality of the application for the simulations is proposed. The optimal solution for the small datasets and best overall results for the medium and large datasets are experimented.

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Authors and Affiliations

  1. Department of Computing, School of Engineering, Computing, and Built Environment, KDU Penang University College, 32 Anson Road, 10400, George Town, Penang, Malaysia

    J. Joshua Thomas &  Justtina

  2. School of Computer Sciences, University Sains Malaysia, 11800, Penang, Gelugor, Malaysia

    Bahari Belaton & Ahamad Tajudin Khader

Authors
  1. J. Joshua Thomas
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  2. Bahari Belaton
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  3. Ahamad Tajudin Khader
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  4. Justtina
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Corresponding authors

Correspondence to J. Joshua Thomas , Bahari Belaton , Ahamad Tajudin Khader or Justtina .

Editor information

Editors and Affiliations

  1. Department of Fundamental and Applied Sciences, Universiti Teknologi Petronas, Tronoh, Perak, Malaysia

    Pandian Vasant

  2. Faculty of Electrical Engineering and Computer Science, VŠB TU Ostrava, Ostrava, Czech Republic

    Ivan Zelinka

  3. Institute of Applied Mathematics, METU, Ankara, Ankara, Turkey

    Gerhard-Wilhelm Weber

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Joshua Thomas, J., Belaton, B., Khader, A.T., Justtina (2019). Visual Analytics Solution for Scheduling Processing Phases. In: Vasant, P., Zelinka, I., Weber, GW. (eds) Intelligent Computing & Optimization. ICO 2018. Advances in Intelligent Systems and Computing, vol 866. Springer, Cham. https://doi.org/10.1007/978-3-030-00979-3_42

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  • DOI: https://doi.org/10.1007/978-3-030-00979-3_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00978-6

  • Online ISBN: 978-3-030-00979-3

  • eBook Packages: EngineeringEngineering (R0)

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