Dettagli Bibliografici
| Autore principale: |
Taglietti, Guilherme Martinelli |
| Data di pubblicazione: |
2025 |
| Natura: |
Bachelor thesis
|
| Lingua: |
por |
| Fonte: |
Repositório Institucional da UPF |
| Download full: |
https://repositorio.upf.br/handle/123456789/9869
|
Riassunto: |
This work investigates how different population-initialization heuristics influence a genetic algorithm for curriculum-based university timetabling. We extend an existing scheduler with three alternatives: a purely random baseline, a heuristic that prioritizes groups of shared classes early in the construction of timetables, and policies that decide when lecture and practice hours of the same subject should be kept together or separated into distinct blocks. The proposed strategies were implemented in the institutional scheduler, executed with real university data and statistically evaluated. The results suggest that the combination of prioritizing shared groups with selective separation of lecture and practice hours leads to promising improvements in the overall scheduling quality. These findings highlight the relevance of heuristic initialization as a practical component for university timetabling and open new directions for further exploration throughout this work. |
