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A Genetic Algorithm Based System with Different Crossover Operators for Solving the Course Allocation Problem of Universities

In: New Trends in Computational Vision and Bio-inspired Computing

Author

Listed:
  • S. Abhishek

    (Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, Department of Computer Science and Engineering)

  • Sunil Coreya Emmanuel

    (Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, Department of Computer Science and Engineering)

  • G. Rajeshwar

    (Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, Department of Computer Science and Engineering)

  • G. Jeyakumar

    (Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, Department of Computer Science and Engineering)

Abstract

Applying the popularly known technologies to solve real world problems are common practice among student researcher community, as it brings deeper understanding of the underlying technology for its further study and improvement. This paper aims at applying the Genetic Algorithm (GA) to solve the course allocation problem of educational institutions. The course allocation problem comprises of p number choices given by n numbers of students for m number of courses. Assigning the maximum number of students with their first or second choice of their courses is a cumbersome task. It is a typical optimization problem, which can be solved in ease by the Evolutionary Algorithms (EAs) such as GA. This paper proposes an automated system which uses GA (with five different crossover operators and three different mutation operators) to solve the course allocation system. A comparative study on the results obtained for different crossover operators is performed. The obtained results are verified with a real time data set collected from our University and validated the superiority of the proposed system.

Suggested Citation

  • S. Abhishek & Sunil Coreya Emmanuel & G. Rajeshwar & G. Jeyakumar, 2020. "A Genetic Algorithm Based System with Different Crossover Operators for Solving the Course Allocation Problem of Universities," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 149-160, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41862-5_14
    DOI: 10.1007/978-3-030-41862-5_14
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