Collaborative Course Assignment Problem to Minimize Unserved Classes and Optimize Education Quality

This work proposes a collaborative course assignment model among universities. It is different from existing studies in educational assignment problems or course timetabling, where the scope is only within the institution or department. In this work, the system consists of several universities. A collaborative approach is conducted so that lecturers exchange is possible and conducted automatically. Each university shares its courses and lecturers. The optimization is conducted to minimize the unserved classes and improve education quality. The cloud-theory based simulated annealing is deployed to optimize the assignment. This model is then benchmarked with two non-collaborative models. The first model’s objective is to minimize the unserved classes only. The second model’s objectives are to minimize the unserved classes and improve education quality. The simulation result shows that the proposed assignment model is better in minimizing the unserved classes and improving education quality. The proposed model reduces 89 to 92 percent of the unserved classes ratio compared with the non-collaborative model.

@article{Kusuma2022,
  title     = {Collaborative Course Assignment Problem to Minimize Unserved Classes and Optimize Education Quality},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {4},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {Purba Daru Kusuma and Ratna Astuti Nugrahaeni},
  doi       = {10.14569/IJACSA.2022.0130421},
  url       = {https://doi.org/10.14569/IJACSA.2022.0130421}
}