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Jihene Tounsi

Informations générales

Jihene Tounsi
Grade

Maître Assistant

Biographie courte

Dr. Jihene Tounsi est Maitre assistante en Informatique de gestion, affiliée à l’IHEC de Carthage où elle exerce en tant qu’Enseignante / Chercheur, et aussi membre Senior du laboratoire SMART-LAB depuis 2010.

Ses enseignements prodigués à la licence BUSINESS COMPUTING portent essentiellement sur la programmation orientée objet et la programmation avancée en JAVA, les systèmes d’exploitation mais aussi l’analyse et la fouille de données en python. De même, elle assure plusieurs cours en Master de recherche et Master professionnel autour de la thématique aide à la décision et Intelligence Artificielle.

Dans le cadre de ses recherches, Dr. Jihène Tounsi, est spécialisée dans l’étude des problématiques liées à la chaîne logistique dans différents domaines tels que les domaines hospitaliers, pharmaceutiques mais aussi industrielles. Ses travaux et ses encadrements portent sur la modélisation du contexte terrain et la proposition d’une solution informatique utilisant des paradigmes de l’intelligence artificielle mais aussi des nouvelles avancées technologiques.

Dans ce contexte scientifique, Dr. Jihène Tounsi a encadré plusieurs travaux de Master de Recherche et co-encadre actuellement des travaux de thèse. Elle a aussi mis en place plusieurs partenariats nationaux et internationaux.

Axes de recherche

Multi Agent System
Artificial Intelligence
Health care
Scheduling problems
Supply Chain management

Publications

  • 2024
    Rihab Chaouch, Jihene Tounsi, Issam Nouaouri, Sabeur Elkosantini

    Mixed Integer Programming For Patient Admission Scheduling in Hospital Network

    This work presents a mixed-integer programming model to optimize patient admission scheduling in hospital networks, with the aim of improving bed assignment and coordination of care., 2024

    Résumé

    The Patient Admission Scheduling (PAS) process involves efficiently managing the admission of patients to specific beds within relevant departments while addressing all their medical needs over a defined time horizon. This study delves into PAS within hospital network, emphasizing the collaborative nature of their interactions. Collaborative interactions are a common challenge in hospitals, where they need to collaborate and share resources to allocate patients to a limited number of beds within a specified timeframe, ensuring all necessary medical conditions are met. To address this challenge, a mixed-integer mathematical programming model for the PAS problem within hospital network is proposed with the aim of minimizing a weighted sum of unsatisfied constraints.

  • Chaima Romdhani, Jihene Tounsi, Said Gattoufi

    Lateral Transshipment in Two-Echelon Inventory Control for Sustainable Pharmaceutical Supply Chain

    Conference: 2023 9th International Conference on Control, Decision and Information Technologies (CoDIT), 2023

    Résumé

    Efficient inventory management (IM) presents an
    important key driver for supply chain (SC) sustainability.
    This latter becomes a crucial concern for decision-makers and
    managers in all domains, particularly in the matter of sensitive
    areas that affect human well-being, namely the pharmaceutical
    industry. Medicines IM for a sustainable Pharmaceutical Sup-
    ply Chain (PSC) brought further particularities compared to
    the traditional SCs. Besides the economic preoccupation, social
    and environmental issues might be considered. In this work, we
    assess the impact of the Lateral Transshipment (LT) strategy on
    the sustainability of the IM process. We compare the total costs
    of two cases, IM with and without LT strategy. We propose an
    IM model that seeks the optimal replenishment order quantity
    of multiple types of products and the shipment time in a
    two-echelon PSC under a centralized setting. The considered
    PSC consists of a pharmaceutical company (PC), a Pharma-
    distributor (PD), and multiple hospitals. The mathematical
    model takes into account the transportation costs including LT
    costs -in the case when LT is included- as well as shortage,
    and products with high deterioration rate costs. We attempt
    to minimize unused medicines leftover by minimizing the
    deterioration rate of products at both distributor and hospital
    sites.

  • Chaima Romdhani, Jihene Tounsi, Said Gattoufi

    Two-echelon Inventory Management for Sustainable Pharmaceutical Supply Chain through Waste Reduction

    10th IFAC Manufacturing Modelling, Management and Control ConferenceAt: Nantes, France, 2022

    Résumé

    Improving sustainability in Pharmaceutical Supply Chain (PSC) becomes theprimary concern for its involved members. It lends major challenges to its management as it haseconomic, social, and environmental responsibilities more weighed than other supply chains.Providing the day-to-day need for medicines must be satisfied while taking into account theuse of the economic resource, customer satisfaction, and the impact of pharmaceutical wasteon the environment. Medicines waste affects healthcare expenses and harms the environment.Therefore, avoiding unused medication leftover through the pharmaceutical chain presents anefficient approach to attaining a sustainable supply of medicines. This article aims to deal withthe sustainability of a PSC by minimizing the deterioration rate of medicines at both distributorand hospitals sites. We propose an inventory management model based on a mixed-integernon-linear program (MINLP) that seeks the optimal replenishment order quantity of multipletypes of products and the shipment time in a two-echelon PSC consisting of a pharmaceuticalcompany (PC), a central pharmacy (CP), and multiple hospitals over a planning horizon, whileconsidering shipment costs, perishability, and shortage constraints.

    Houyem Ben Hassen, Jihene Tounsi, Rym Ben Bachouch, Sabeur Elkosantini

    Case-based reasoning for home health care planning considering unexpected events

    IFAC-PapersOnLine, 55(10), 1171-1176, 2022

    Résumé

    In recent years, Home Health Care (HHC) has gained popularity in different countries around the world (e.g. France, US, Germany, etc.). The HHC consists in providing medical services to patients at home. During the HHC service, caregivers’ planning may be disrupted by some unexpected events (e.g. urgent request, caregiver absence, traffic congestion, etc.), which makes HHC activities infeasible. This paper addresses the daily HHC routing and scheduling problem by considering unpredicted events. To solve this problem, we propose a Case-Based Reasoning (CBR) methodology. Our purpose is to create the HHC case base which contains the knowledge about the perturbation.

  • Houyem Ben Hassen, Jihene Tounsi, Rym Ben Bachouch

    An Artificial Immune Algorithm for HHC Planning Based on multi-Agent System

    Procedia Computer Science, 164, 251-256, 2019

    Résumé

    This paper presents the home health care routing and scheduling problem as the vehicle routing problem with time windows (VRPTW). we propose a dynamic approach for home care planning to ensure the continuity of care for patients. The proposed approach aims to optimize the care plan route of each caregiver according to their skills, availabilities and preferences. We aim also to minimize the violation of time windows in order to maximize patient and caregiver’s satisfaction. The optimal plan route is generated with a population-based algorithm which is the Artificial Immune Algorithm (AIS). A multi-agent approach is used to ensure communication and coordination between the different actors.

Projets