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Static and Dynamic Parameter Settings of Accelerated Particle Swarm Optimisation for Solving Course Scheduling Problem

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Cooperative Design, Visualization, and Engineering (CDVE 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12341))

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Abstract

The university course timetabling problem (UCTP) is one of the most challenging scheduling problems and also classified to be a Non-deterministic Polynomial (NP)-hard problem. An Accelerated Particle Swarm Optimisation based Timetabling (APSOT) program was developed to generate the best-so-far timetables with the minimal total operating costs. Two new variants of Accelerated Particle Swarm Optimisation (APSO) including Static and Dynamic (S-APSO and D-APSO) were proposed and embedded into the APSOT tool. The analysis of variance on the experimental results indicated that the main effects and interactions of D-APSO were statistically significant with a 95% confidence interval. The S-APSO and Maurice Clerc PSO (MCPSO) outperformed the other variants of PSO for most datasets whereas the execute times required by all variants of PSO were slightly different.

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Acknowledgements

The second author would like to acknowledge Naresuan University Graduate School for granting Ph.D. scholarship. This work was also part of research project supported by the Thailand Science Research and Innovation (TSRI) and Office of the Higher Education Commission (OHEC) under grant number MRG6080066.

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Authors and Affiliations

  1. Faculty of Industrial Technology, Pibulsongkram Rajabhat University, Phitsanulok, Thailand

    Thatchai Thepphakorn

  2. Centre of Operations Research and Industrial Applications (CORIA), Department of Industrial Engineering, Faculty of Engineering, Naresuan University, Phitsanulok, 65000, Thailand

    Saisumpan Sooncharoen & Pupong Pongcharoen

Authors
  1. Thatchai Thepphakorn
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  2. Saisumpan Sooncharoen
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  3. Pupong Pongcharoen
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Correspondence to Pupong Pongcharoen .

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  1. University of the Balearic Islands, Palma, Mallorca, Spain

    Yuhua Luo

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Thepphakorn, T., Sooncharoen, S., Pongcharoen, P. (2020). Static and Dynamic Parameter Settings of Accelerated Particle Swarm Optimisation for Solving Course Scheduling Problem. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2020. Lecture Notes in Computer Science(), vol 12341. Springer, Cham. https://doi.org/10.1007/978-3-030-60816-3_40

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  • DOI: https://doi.org/10.1007/978-3-030-60816-3_40

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  • Online ISBN: 978-3-030-60816-3

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