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DNA Self-assembly Computing Model for the Course Timetabling Problem

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Recent Advances in Data Science (IDMB 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1099))

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Abstract

The course timetabling problem is a highly-constrained combination problem, which cannot be solved in polynomial time by a deterministic algorithm. In this paper, a DNA self-assembly computing model was presented to solve a course timetabling problem which can meet all students’ course-choosing requests using the least number of classes. There are three subsystems in this DNA self-assembly computing model, which are initial solution space generation system, detection system, and time slots counting system. The results demonstrated that the university timetable self-assembly system can obtain the solution using O(n2) tiles.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (61632002, 61972109) and the Natural Science Foundation of Guangdong Province of China (2018A030313380).

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Authors and Affiliations

  1. Institute of Computing Science and Technology, Guangzhou University, Guangzhou, 510006, Guangdong, China

    Zheng Kou & Xiaoli Qiang

  2. College of Computer Science, South-Central University for Nationalities, Wuhan, 430074, Hubei, China

    Zhibao Xing & Wenfei Lan

Authors
  1. Zheng Kou
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  2. Zhibao Xing
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  3. Wenfei Lan
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  4. Xiaoli Qiang
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Corresponding author

Correspondence to Xiaoli Qiang .

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Editors and Affiliations

  1. Fordham University, New York, NY, USA

    Henry Han

  2. Guangxi University, Nanning, China

    Tie Wei

  3. Guangzhou University, Guangzhou, China

    Wenbin Liu

  4. Jiangsu University, Zhenjiang, China

    Fei Han

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Kou, Z., Xing, Z., Lan, W., Qiang, X. (2020). DNA Self-assembly Computing Model for the Course Timetabling Problem. In: Han, H., Wei, T., Liu, W., Han, F. (eds) Recent Advances in Data Science. IDMB 2019. Communications in Computer and Information Science, vol 1099. Springer, Singapore. https://doi.org/10.1007/978-981-15-8760-3_18

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  • DOI: https://doi.org/10.1007/978-981-15-8760-3_18

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-8759-7

  • Online ISBN: 978-981-15-8760-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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