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Genetic Algorithms for Scheduling Examinations

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Advanced Information Networking and Applications (AINA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 227))

Abstract

The range of problems to which genetic algorithms have been applied is quite broad. Timetable scheduling is a complex optimization problem. The purpose is to solve this problem by using genetic algorithms. There are two implementations for this problem: the first one solves the complete issue, and the second one divides the problem into two phases and solves the second phase. The results show that the second implementation has better solutions than the first one.

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Author information

Authors and Affiliations

  1. College of Engineering and Science, Victoria University Sydney, Sydney, Australia

    Farshid Hajati & Soheila Gheisari

  2. Department of Mechatronics Engineering, Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran

    Alireza Rezaee

Authors
  1. Farshid Hajati
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  2. Alireza Rezaee
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  3. Soheila Gheisari
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Corresponding author

Correspondence to Farshid Hajati .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Computer Science, Ryerson University, Toronto, ON, Canada

    Isaac Woungang

  3. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

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© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Hajati, F., Rezaee, A., Gheisari, S. (2021). Genetic Algorithms for Scheduling Examinations. In: Barolli, L., Woungang, I., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2021. Lecture Notes in Networks and Systems, vol 227. Springer, Cham. https://doi.org/10.1007/978-3-030-75078-7_52

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