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.

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. (Intervento presentato al convegno 8th International Conference on Variable Neighborhood Search, ICVNS 2021 tenutosi a on-line nel 2021) [10.1007/978-3-030-69625-2_11].

Scheduling of Patients in Emergency Departments with a Variable Neighborhood Search

Alves de Queiroz T.
;
Iori M.;
2021

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.
2021
8th International Conference on Variable Neighborhood Search, ICVNS 2021
on-line
2021
12559
138
151
Alves de Queiroz, T.; Iori, M.; Kramer, A.; Kuo, Y. -H.
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. (Intervento presentato al convegno 8th International Conference on Variable Neighborhood Search, ICVNS 2021 tenutosi a on-line nel 2021) [10.1007/978-3-030-69625-2_11].
File in questo prodotto:
File Dimensione Formato  
ED_ICVNS_2020.pdf

Accesso riservato

Descrizione: Versione post-referaggio
Tipologia: Versione dell'autore revisionata e accettata per la pubblicazione
Dimensione 297.02 kB
Formato Adobe PDF
297.02 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1243419
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? ND
social impact