Hybrid simulation modelling of emergency departments for resource scheduling - Université de Lorraine Accéder directement au contenu
Article Dans Une Revue Journal of Simulation Année : 2024

Hybrid simulation modelling of emergency departments for resource scheduling

Résumé

This paper addresses the problem of resource scheduling of emergency departments in an uncertain environment. An innovative approach based on Agent-Based Simulation (ABS) and Discrete Event Simulation (DES) is proposed. To do so, this paper first proposes a framework integrating ABS and DES. Subsequently, we provide a detailed description of the DES and ABS parts of the model of the ED. Five combinations of strategies – namely, “FIFO+Random” (i:e:FIFO: the queue of patients operates in FIFO; Random: the patients are randomly assigned to doctors), “FIFO+Centralised”, “Random+Centralised” (“Centralised” implies the assignment of the most appropriate doctor to a patient is only determined by the Platform agent via optimising all the resources), “Random+Random” and “Autonomous” – are implemented to schedule the resources of the ED. Finally, experiments analyse the efficiency of the five combinations of strategies on the duration of patients’ stay. The results show that “FIFO +Centralised” outperforms others regarding the average for the duration of patients’ stay without hospitalisation: 3.75% of the time has been saved; “Random+Centralised” outperforms others regarding the average for the duration of patients’ stay with hospitalisation: 0.57% of the time has been saved.
Fichier sous embargo
Fichier sous embargo
0 4 29
Année Mois Jours
Avant la publication
lundi 16 septembre 2024
Fichier sous embargo
lundi 16 septembre 2024
Connectez-vous pour demander l'accès au fichier

Dates et versions

hal-04031528 , version 1 (08-02-2024)

Identifiants

Citer

Yinling Liu, Thierry Moyaux, Guillaume Bouleux, Vincent Cheutet. Hybrid simulation modelling of emergency departments for resource scheduling. Journal of Simulation, inPress, pp.Latest Article. ⟨10.1080/17477778.2023.2187321⟩. ⟨hal-04031528⟩
83 Consultations
3 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More