University class timetables assigned through evolutionary algorithms

Authors

  • José Ma. Mejía Caballero Universidad de La Guajira, Riohacha (Colombia)
  • Carlos Paternina Arboleda Universidad del Norte, Barranquilla (Colombia)

DOI:

https://doi.org/10.26507/rei.v5n9.15

Keywords:

subjects, scheduling, classrooms.

Abstract

Allocation of class schedules is a complex problem due to the amount of restrictions that it poses and the criteria that are applied to the process. The allocation of class schedules and classrooms is an expert system that reproduces the knowledge gained from years of handling academic processes. There are universities that, in the process of allocation of class schedules and classrooms, generate conflicts between subjects, produce long intervals between class sessions, show geographical distances for students among teaching shifts and reveal dissatisfaction expressed by teachers and students. The set of restrictions imposed by the philosophy of the university introduces some complex restrictions designed to minimize the time students spend in the university campus and the conflicts among subjects. This research work seeks to find a solution for a practical problem of allocation of class schedules, a problem classified as a matter of timetabling which is often considered a common problem in the academic context.

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Author Biographies

José Ma. Mejía Caballero, Universidad de La Guajira, Riohacha (Colombia)

Ms.C. Ingeniero Industrial, Magíster en Ingeniería Industrial, Director de Sistemas y Docente Catedrático de la Universidad de La Guajira, Km 5 Vía a Maicao, Riohacha – La Guajira, Ponente en el XVI Congreso Latino Ibero Americano de Investigación de Operaciones – Claio 2008.

Carlos Paternina Arboleda, Universidad del Norte, Barranquilla (Colombia)

Ph.D., Ingeniero Industrial, Ph.D. en Ingeniería Industrial de la FIU (E.U.), Profesor de Tiempo Completo del Departamento de Ingeniería Industrial de la Universidad del Norte, Km 5 Vía a Puerto Colombia, Barranquilla – Atlántico, Intelligent Dynamic Control Policies..., II E Transactions (to Appear) - Kluwer Academics, 9/1/2000.

References

Bardadym V. (1996). Computer Aided School and University Timetabling. The New Wave. Lecture Notes in Computer Science Series, Vol. 1153, pp. 22-45.

Burke E., De Werra D. y Kingston J. (2003). Applications to Timetabling. Gross y Yellen Editores and Handbook of Graph Theory, pp. 445-474.

Burke E., Jackson K., Kingston J. y Weare R. (1998). Automated University Timetabling: The State of the Art. The Computer Journal. Vol. 40 Nº 9, pp. 565-571.

Carter M. y Laporte G. (1998). Recent Developments in Practical Course Timetabling. Lecture Notes in Computer Science. Vol. 1408, pp. 3-19.

De Werra D. (1985). An Introduction to Timetabling. European Journal of Operational Research. Vol. 19, pp. 151-162.

Published

2012-02-15

How to Cite

Mejía Caballero, J. M., & Paternina Arboleda, C. (2012). University class timetables assigned through evolutionary algorithms. Revista Educación En Ingeniería, 5(9), 140–149. https://doi.org/10.26507/rei.v5n9.15

Issue

Section

Engineering and Development

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