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Investigation of Data Regularization and Optimization of Timetables by Lithuanian High Schools Example

In: Advances in Stochastic and Deterministic Global Optimization

Author

Listed:
  • Jonas Mockus

    (Vilnius University)

  • Lina Pupeikiene

    (Vilnius University)

Abstract

In practice, we must first assign teachers and students to subject-groups for school applications. In the Lithuanian high schools, the number of subject-groups can be very large, since students are free to select just a small subset of optional subjects. The experimental investigation of this chapter did show that in such conditions, some regularization of subject-groups is needed for prior to optimization. The regularization is a sequential elimination of the timetable-breakers. A timetable-breaker is a student or teacher the presence of which in a subject-group is most harmful for the timetable. The automatic elimination of breakers is difficult due to many subjective factors. In practice it is done by an expert trying to change the subject-group accordingly. In the case of teachers the personal communication is used, if the group changes do not help. The application of optimization algorithms for timetabling data regularization is the new result of this work. New also is the experimental investigation applying optimization algorithms in 39 Lithuanian high schools.

Suggested Citation

  • Jonas Mockus & Lina Pupeikiene, 2016. "Investigation of Data Regularization and Optimization of Timetables by Lithuanian High Schools Example," Springer Optimization and Its Applications, in: Panos M. Pardalos & Anatoly Zhigljavsky & Julius Žilinskas (ed.), Advances in Stochastic and Deterministic Global Optimization, pages 167-180, Springer.
    • Handle: RePEc:spr:spochp:978-3-319-29975-4_9
    DOI: 10.1007/978-3-319-29975-4_9
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