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Symposium on Machine Learning and Metaheuristics Algorithms, and Applications

SoMMA 2020: Machine Learning and Metaheuristics Algorithms, and Applications pp 131–145Cite as

Exam Seating Allocation to Prevent Malpractice Using Genetic Multi-optimization Algorithm

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1366))

Abstract

Despite unceasing debate about it’s pros and cons, exams and standardized testing have emerged as the main mode of evaluation and comparison in our increasingly competitive world. Inevitably, some examinees attempt to illegally gain an unfair advantage over other candidates by indulging in cheating and malpractice. Even a single case of examination malpractice can destroy an Examination body’s credibility and even lead to costly and time-consuming legal proceedings.

Our paper attempts to strategically allot examinees in specific seats and rooms, such as to mitigate the overall probability of malpractice. It involves examining multiple crucial factors such as subject similarity, distancing between examinees, and human field of vision to find the most optimal seating arrangement. We have exploited the property of Evolutionary Genetic Algorithms to find globally optimal or close to optimal solutions in an efficient time for this otherwise NP-complete permutation problem.

Supported by PES University.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, PES University, Bengaluru, Karnataka, India

    Madhav M. Kashyap, S. Thejas, C. G. Gaurav & K. S. Srinivas

Authors
  1. Madhav M. Kashyap
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  2. S. Thejas
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  3. C. G. Gaurav
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  4. K. S. Srinivas
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Corresponding authors

Correspondence to Madhav M. Kashyap , S. Thejas , C. G. Gaurav or K. S. Srinivas .

Editor information

Editors and Affiliations

  1. Indian Institute of Information Technology and Management - Kerala, Trivandrum, India

    Sabu M. Thampi

  2. University of Florida, Gainesville, FL, USA

    Selwyn Piramuthu

  3. Providence University, Taichung, Taiwan

    Kuan-Ching Li

  4. Università degli Studi di Firenze, Florence, Italy

    Stefano Berretti

  5. Wrocław University of Technology, Wrocław, Poland

    Michal Wozniak

  6. Hankuk University of Foreign Studies, Yongin, Korea (Republic of)

    Dhananjay Singh

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Cite this paper

Kashyap, M.M., Thejas, S., Gaurav, C.G., Srinivas, K.S. (2021). Exam Seating Allocation to Prevent Malpractice Using Genetic Multi-optimization Algorithm. In: Thampi, S.M., Piramuthu, S., Li, KC., Berretti, S., Wozniak, M., Singh, D. (eds) Machine Learning and Metaheuristics Algorithms, and Applications. SoMMA 2020. Communications in Computer and Information Science, vol 1366. Springer, Singapore. https://doi.org/10.1007/978-981-16-0419-5_11

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  • DOI: https://doi.org/10.1007/978-981-16-0419-5_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-0418-8

  • Online ISBN: 978-981-16-0419-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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