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  1. Pubblicazioni

Scheduling of Patients in Emergency Departments with a Variable Neighborhood Search

Contributo in Atti di convegno
Data di Pubblicazione:
2021
Citazione:
Scheduling of Patients in Emergency Departments with a Variable Neighborhood Search / Alves De Queiroz, T.; Iori, M.; Kramer, A.; Kuo, Y. -H.. - 12559:(2021), pp. 138-151. ( 8th International Conference on Variable Neighborhood Search, ICVNS 2021 on-line 2021) [10.1007/978-3-030-69625-2_11].
Abstract:
The dynamic scheduling of patients to doctors in an emergency department environment is tackled in this work. We consider the case in which patients arrive dynamically during the working hours, and the objective is to minimize the weighted tardiness. We propose a greedy heuristic based on priority queues and a general variable neighborhood search (GVNS). In the greedy heuristic, patients are scheduled by observing their urgency, while in the GVNS, the schedule is optimized every time a patient arrives. The GVNS uses six neighborhood structures and a variable neighborhood descent to perform the local search. The GVNS also handles the static problem whose solution can be used as a reference for the dynamic one. Computational results on 80 instances show that using the GVNS better approximates the static problem, besides giving an overall reduction of 66.8% points over the greedy heuristic.
Tipologia CRIS:
Relazione in Atti di Convegno
Keywords:
Dynamic scheduling; Emergency department; Health care; Variable neighborhood search
Elenco autori:
Alves De Queiroz, T.; Iori, M.; Kramer, A.; Kuo, Y. -H.
Autori di Ateneo:
IORI MANUEL
Link alla scheda completa:
https://iris.unimore.it/handle/11380/1243419
Titolo del libro:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pubblicato in:
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
Journal
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
Series
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