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

Khouloud DORGHAM

ATER
Member of the research themes:
Contact information:

Revue Internationale avec Comité de Lecture

2022
International journal with review committee
DOI
Collaborative hospital supply chain network design problem under uncertainty
Operational Research International Journal, 07/2022

Conférence Internationale avec Comité de Lecture

2022
International conference with review committee
Fuzzy Programming Approach for Collaborative Supply Chain under Uncertain Demand
The 6th IEEE International Conference on Logistics Operations Management, GOL2022, Strasbourg, France, 29th June to 1st July, 06/2022
A collaborative supply chain network design within a territory hospital group
13th International Conference on Modeling, Optimization and Simulation, MOSIM'2020, Agadir, Maroc, 12-14 November 2020, 11/2020
A Hybrid Simulated Annealing Approach for the Patient Bed Assignment Problem
Proceedings of the 23rd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, KES 2019, pp 408-417, Budapest, Hungary, 4-6 September 2019, 09/2019

Conférence Nationale avec Comité de Lecture

Mutualisation des flux logistiques au sein d’un Groupement Hospitalier de Territoire
10ème Conférence Francophone en Gestion et Ingénierie des Systèmes Hospitaliers, GISEH2020, Valenciennes, France, UPHF, 26-29 Octobre 2020, 10/2020
Pooling of logistics flows within a Territory Hospital Group
21 congrès annuel de la société Française de Recherche Opérationnelle et d’Aide à la Décision, ROADEF 2020, Montpellier, France, Université de Montpellier, 02/2020

Chapitre de livre

A Decision Support System for Smart Health Care
IoT and ICT for Healthcare Applications, pp 85--98, Springer International Publishing, ISBN 978-3-030-42934-8, 08/2020

Author of the Ph.D. thesis "Optimization of Storage and Distribution Schemes under Uncertainty: Application to Territory Hospital Group Stores"

2019 - 2022

Nowadays, healthcare systems are increasingly constrained by limited resources and a rising interest in efficiency. In this context, the French government has implemented new incentive programs to improve logistics activities within hospitals and increase the efficiency of the health system. These leads to cost savings, improved patient care quality, and well-being of nursing staff. Indeed, several collaborative health reforms with different objectives and legal structures have developed in recent years, in particular, with the creation of Territorial Hospital Groups (THG) in 2016. To optimize and rationalize their deployments on the territory, these new restructurings require efficient decision support tools. This thesis was inspired by the opportunity provided by the THG structural project to address the optimization of several problems arising from hospital logistics at the strategic, tactical, and operational decision-making levels. The objective is to determine the optimal scenarios for the allocation, storage, and distribution of products consumed by the care units of the THG. This study investigated two major problems in logistics pooling. On the one hand, to deal with strategic decisions, we are interested in the allocation of products to THG warehouses and stores in order to organize the logistical flows between them and the care units. On the other hand, tactical and operational decisions were jointly modeled from the perspective of a new rich variant of the Inventory Routing Problem (IRP) in a two-echelon, multi-product, and multi-depot system while allowing split deliveries. Unexpected events in the healthcare domain may occur as a result of seasonal fluctuations or epidemics, affecting either of the two investigated problems. Hence, we proposed a fuzzy chance-constrained programming approach to study the relevance of handling uncertainty related to care unit demand and its economic impact. Several methods for the optimization of inventory and product distribution are proposed: an exact method (integer linear programming), a constructive heuristic, and a meta-heuristic approach entitled GVNS (General Variable Neighborhood Search). Different tests were developed on a randomly generated set of instances to demonstrate the performance of the proposed methods.