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International Conference on Swarm Intelligence

ICSI 2019: Advances in Swarm Intelligence pp 363–373Cite as

Evaluation of Genetic Algorithm and Hybrid Genetic Algorithm-Hill Climbing with Elitist for Lecturer University Timetabling Problem

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11655))

Abstract

Lecturer university timetabling is an NP-hard real-world problem still needs great attention. The occurrences of the creation of timetable in every university prior to semester starts are compulsory. Its inclusively must cater both hard and soft constraints to satisfy both lecturers and students as the space and time are highly concerned. Genetic Algorithm and Hybrid Genetic Algorithms-Hill Climbing with embedded with elitist mechanism are evaluated with the use of real data sets. The findings have shown Hybrid Genetic Algorithms-Hill Climbing with elitist outperformed Genetic Algorithm with elitist in obtaining an optimal solution. The beauty element offered by Hill Climbing seeking local best individual of the population has given fast convergences with the capability avoiding local optimum. In future, more soft constraints identification of a real problem of lecturer timetabling problem should very much considered as to ensure satisfactions of lecturers and students.

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Acknowledgement

Universiti Teknologi MARA a for the grant of 600-IRMI/PERDANA 5/3 BESTARI (096/2018) as well as Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Malaysia for providing essential support and knowledge for the work.

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Authors and Affiliations

  1. Advanced Analytic Engineering Center (AAEC), Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia

    Marina Yusoff

  2. Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia

    Nurhikmah Roslan

Authors
  1. Marina Yusoff
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  2. Nurhikmah Roslan
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Corresponding author

Correspondence to Marina Yusoff .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

  3. Shenzhen University, Shenzhen, China

    Ben Niu

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Yusoff, M., Roslan, N. (2019). Evaluation of Genetic Algorithm and Hybrid Genetic Algorithm-Hill Climbing with Elitist for Lecturer University Timetabling Problem. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2019. Lecture Notes in Computer Science(), vol 11655. Springer, Cham. https://doi.org/10.1007/978-3-030-26369-0_34

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  • DOI: https://doi.org/10.1007/978-3-030-26369-0_34

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26368-3

  • Online ISBN: 978-3-030-26369-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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