Aplicación web para la asignación automática de horarios docentes mediante algoritmos genéticos

César Octavio González- Camargo; Justmary Del Carmen Anderson Fermín; José Chiru-Figueroa

doi:10.48204/j.colonciencias.v13n2.a9267

Submitted January 23, 2026

Published 2026-07-07

Artículos

Vol. 13 No. 2 (2026): Revista Colón Ciencias, Tecnología y Negocios

Web application for automatic teacher timetabling using genetic algorithms

César Octavio González- Camargo⁺⁻
Justmary Del Carmen Anderson Fermín ⁺⁻
José Chiru-Figueroa⁺⁻

DOI https://doi.org/10.48204/j.colonciencias.v13n2.a9267

PDF (Español (España))

References

DOI: 10.48204/j.colonciencias.v13n2.a9267

Published: 2026-07-07

How to Cite

González- Camargo, C. O., Anderson Fermín , J. D. C., & Chiru-Figueroa, J. (2026). Web application for automatic teacher timetabling using genetic algorithms. Revista Colón Ciencias, Tecnología Y Negocios, 13(2), 17–37. https://doi.org/10.48204/j.colonciencias.v13n2.a9267

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Abstract

In higher education institutions, teacher scheduling is a key process for ensuring academic continuity. In this context, this study addressed the problem of manual teacher scheduling in these environments, characterized by high combinatorial complexity, susceptibility to errors, and high administrative time consumption. The objective was to develop and validate a web application for the automatic assignment of teaching schedules using genetic algorithms. The methodology applied was experimental and quantitative, structured in phases of analysis, design, implementation, and evaluation. The system was developed using a dockerized architecture based on Python and SQL Server, integrating a multi-objective fitness function to manage hard (availability) and soft (equity) constraints. The results obtained after testing with real data showed that the system reduced planning time by more than 95%, eliminated schedule conflicts in the evaluated scenario, and improved the balance of academic workload among teachers. Consequently, the proposed solution is viable, efficient, and scalable for optimizing academic management.

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References

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