Laboratoire de Génie Informatique et d’Automatique de l’Artois

Seifeddine ABDELHAK

ATER
(Left the LGI2A in 2022)
Member of the research themes:

Revue Internationale avec Comité de Lecture

2023
International journal with review committee
DOI
Seifeddine ABDELHAK -- Issam NOUAOURI -- Saoussen KRICHEN -- Gilles GONCALVES
Minimization of Makespan and Total Completion Time for Hybrid Job Shop Scheduling Problem using Genetic Approaches
International Journal on Artificial Intelligence Tools, 03/2023

Conférence Nationale avec Comité de Lecture

2019
French conference with review committee
More info
Seifeddine ABDELHAK -- Issam NOUAOURI -- Gilles GONCALVES
A genetic algorithm for patient scheduling in emergency department
20ème congrès annuel de la société Française de Recherche Opérationnelle et d’Aide à la Décision, ROADEF 2019, Le Havre, France, Université du Havre, 02/2019
2018
French conference with review committee
More info
Jean-Christophe NICOLAS -- Seifeddine ABDELHAK -- Raoul DERISBOURG -- Issam NOUAOURI -- Gilles GONCALVES
Méthode et outil pour la rationalisation des magasins et des flux au sein des Groupements Hospitaliers de Territoire
9ème Conférence Francophone en gestion et ingénierie des systèmes hospitaliers, GISEH 2018, Genève, Suisse, 27-29 Août 2018, 08/2018

Author of the Ph.D. thesis "Dynamic scheduling of patients in emergency departments"

2017 - 2021

An Emergency Department (ED) represents the gateway to every health care cen- ter. It opens 24 hours per day and 7 days per week. During the last years, the ED have benefited special attention. The goal is to offer a better quality of service to the pa- tient. In fact, the number of visits to EDs has greatly increased causing overcrowding and dissatisfaction of patients. Improving its efficiency as well as patients’ treatment is a significant challenge.
This thesis focuses on the scheduling of patients in ED. The problem is considered as a Hybrid Job Shop Problem (HJSP). The objective is to find a schedule that minimizes the total completion time or the makespan. This problem is a N P -hard combinatorial optimization problem. So, we developed and validated a Genetic Algorithm (GA) and a Hybrid Genetic Algorithm (HGA) by testing them on benchmarks found in the literature on manufacturing systems. The performances obtained were compared to existing HJSP approaches of the literature.
Then, we adapted and applied both algorithms to plan patient journeys in a Tunisian hospital ED, in which, we collected data. In ED, the objective is to min- imize patient waiting times in order to reduce the problem of overcrowding while taking into account the categories of patients. Particular attention must be paid to the categories of critical patients who must be quickly taken care of by a team. Initially, we only considered the expected patients and we simulated several scenarios to verify and measure the effectiveness of an approach based on patient categories, assuming that all data are perfectly known. Then, in a second step, considering all the reality of an emergency (i.e. with dynamics events), we took into account the uncertainties related to the patient arrivals and the duration of treatment provided by caregivers. Finally, we considered unexpected patients whose arrivals are unpredictable. To deal with these dynamic events, we studied a predictive and reactive planning strategy based on the previous algorithms. All the approaches were tested compared to the existing strategy based on the principle of "first come, first served" combined with a category priority rule which is usually found in emergency services. Results show that our approaches can improve the usual strategy when the rate of dynamic patients is under 50%.

ARS-GHT

2017 - 2019

Logistique hospitalière de territoire – Des établissements aux Groupements Hospitaliers Territoriaux

Summary :

Depuis juillet 2016, les hôpitaux publics français ont obligation de rejoindre un groupement hospitalier de territoire (GHT), afin d’y développer coopérations, mutualisations et économies d’échelle.
Le projet consiste à fournir un outil d’aide à la décision pour la mise en place d’une logistique mutualisée au sein de ces GHT.