Houyem Ben Hassen

Informations générales

Grade

Post Doc

Biographie courte

Houyem Ben Hassen is a Doctor in Business Computing. She holds their Ph.D. from the Higher Institute of Management of Tunis in 2025. She received her Master’s Degree in System Information and Decision Support in 2020 and her Applied Bachelor’s Degree in Management Information Systems in 2017, both from the Higher Institute of Management of Sousse.

Her research focuses on the optimization of routing and scheduling, machine learning algorithms for real-time scheduling problems, and multi-agent systems.

Axes de recherche

Metaheuristics

Scheduling problems

Optimization

Health care

Machine Learning

Multi Agent System

Publications

2022

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.
2019

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.