An expert system based on data mining and linear integer programming to support the timetabling design and courses assignment in higher education

  • Daniel Calle-López Universidad Politécnica Salesiana
  • Javier Cornejo-Reyes Universidad Politécnica Salesiana
  • Fernando Pesántez-Avilés Universidad Politécnica Salesiana
  • Mónica Rodas-Tobar Universidad del Azuay
  • César Vásquez-Vásquez Universidad Politécnica Salesiana
  • Vladimir Robles-Bykbaev Universidad Politécnica Salesiana


Commonly, the most of organizations tend to manage the timetables of their employees according to traditional guidelines (imposing an 8-hour work day). The primary objective of this approach is controlling some variables such as the attendance and absenteeism of the employees, and even, in some cases considering this situation as work efficiency. However, the new organizational tendencies have broken specific paradigms based on mechanistic orientation, trying to create a new horizon towards the construction of organic and dynamic organizations. For these reasons, in this paper, we present an expert system based on integer linear programming and data mining with the aim of addressing the problem of assigning courses to teachers and timetabling (considered an NP-complete problem). The preliminary results are encouraging, given that the system was able to assign courses on a database consisting off 133.000 registers of teachers, and at the same time, generate timetables with minimal computational costs.


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How to Cite
Calle-López, D., Cornejo-Reyes, J., Pesántez-Avilés, F., Rodas-Tobar, M., Vásquez-Vásquez, C., & Robles-Bykbaev, V. (2018). An expert system based on data mining and linear integer programming to support the timetabling design and courses assignment in higher education. Enfoque UTE, 9(1), pp. 102 - 117.
Computer Science, ICTs