CHAIEB Marouene

Marouene

CHAIEB

chaieb.marouene@live.fr

moury.7up@gmail.com

Assistant contractuel

Departement statistiques et analyses,

Tél:

00966501155645

cv_of_marouene_chaieb.pdf

Cursus universitaire

Licence fondamentale en informatique de gestion

2010

Institut Superieur de Gestion de Tunis

Mastere en informatique de Gestion (MIS) de la specialite methode inteligentes d aide a la decision (MIAD)

2012

Institut Superieur de Gestion de Tunis

Doctorant en informatique de Gestion (quatrieme annee)

2014

Institut Superieur de Gestion de Tunis

Domaines de recherche

Combinatorial Optimization Problems; Supply chain management; Operational Research; Decision support systems; Artificial Intelligence.

Expérience professionnelle

Assistant

du 07/10/2012 a aujourd hui

Universite de Salmen Ibn AbdelAzizAl Kharej, Arabie Saoudite.

Assistant

01/02/2012 - 30/07/2012

Institut Superieur de Gestion de Tunis

Programmeur

01/10/2010- 31/10/2011

Bayer Health Care- Les bergrs du Lac

Stagiaire a Bayer Health Care

01/07/2010-30/09/2010

Bayer Health Care - Les berges du Lac

Tache: Conception et implementation d une application de gestion des commandes

Stagiaire a Tunisie Tradenet

01/02/2010-20/05/2010

Tunis

Tache: Conception et implementation d une application d achat en ligne

Stagiaire au Banque Internationale Arabe de Tunisie (BIAT)

07/07/2009-31/08/2009

Tunis

Tache: la conception et l implementation d une application de gestion d integration des modeules de l SAP aux besoin de la banque.

Stagiaire a International Bio Services

01/06/2008-31/06/2008

Tunis

Tache: la conception et l implementation d une application de gestion des materiels informatique.

Stagiaire a International Form

07/07/2008-30/08/2008

Tunis

Tache: la conception et l implementation d une application de gestion de conge avec la notion du work flow

Modules enseignés

Assistant a l ISG

ASD

Assistant a l Universite de Selmen Ibn AbdelAziz

Data Base Computer architecture Software Engineering Operation Systems ICDL

Activités administratives

Chef de departement des statistiques et des analyses de l universite de Sattam Ibn AbdelAziz

Thèse de doctorat

A generic hierarchical problems solving algorithm for combinatorial optimization problems: the home care scheduling problem by example

Directeurs:

Khaled Mellouli (ISG, Tunis)

, Jaber Jemai (ISI, Tunis)

Année soutenance: Théses de doctorat en cours.

ISG de Tunis

Mémoire de mastère / DEA

The home care scheduling problem: a modeling and solving issue

Directeurs:

Khaled Mellouli (ISG, Tunis)

, Jaber Jemai (ISI, Tunis)

Année soutenance: 2011/2012

ISG de Tunis

master_degree_report.pdf

Publications

Conférences Internationales avec comité de lecture et actes

Marouene CHAIEB

, Jaber JEMAI

, Khaled Mellouli

A hierarchical modeling and solving approach for the Home Health Care Scheduling Problem,

, 2016

[BibTeX...]

The Home Health Care Scheduling Problem (HCSP) is an optimization problem representing an emerging approach for delivering health care services. Home health care consists of assigning a set of caregivers or nurses to provide health service to patients at their home. Nowadays, such kind of services are highly requested due to the increasing of number of elderly peoples who need to be treated at their homes. Moreover, the HCSP solution will lead to decrease the usage of hospital facilities and the may be used to accommodate more critical cases. Additionally, some patients need long life treatment that should be provided periodically by skilled personnel without a need to go to hospitals. The HCSP was extensively studied and a variety of approaches were proposed for modeling and solving [1]. In this paper, we present a new approach to solve the HCSP. We propose a hierarchical model of the home health care scheduling problem that consists of dividing the problem into a set of interconnected sub problems easier to solve. The obtained model is a result of the application of the Hierarchical Modeling Approach proposed in [2]. The HCSP hierarchical model will be solved using different algorithms to solve each sub problem at each level respecting the type of inter-connection between them. In the next sections, we detail the proposed approaches for modelling and solving the HCSP.

Marouene CHAIEB

, Jaber JEMAI

, Khaled Mellouli

Decomposability Conditions of Combinatorial Optimization Problems,

Combinatorial Optimization Problems (COP) are generally complex and difficult to solve as a single monolithic problem. Thus, the process to solve the main initial COP may pass through solving intermediate problems and then combining the obtained partial solutions to find initial problem’s global solutions. Such intermediate problems are supposed to be easier to handle than the initial problem. To be modeled using the hierarchical optimization framework, the master problem should satisfy a set of desirable conditions. These conditions are related to some characteristics of problems which are: multi-objectives problem, over constrained problems, conditions on data and problems with partial nested decisions. For each condition, we present supporting examples from the literature where it was applied. This paper aims to propose a new approach dealing with hard COPs particularly when the decomposition process leads to some well-known and canonical optimization sub-problems. , 2015

decomposability_conditions_of_combinatorial_optimization_problems.pdf

Marouene CHAIEB

, Jaber JEMAI

, Khaled Mellouli

On the Relationships Between Sub Problems in the Hierarchical Optimization Framework,

In many optimization problems there may exist multiple ways in which a particular hierarchical optimization problem can be modeled. In addition, the diversity of hierarchical optimization problems requires different types of multilevel relations between sub-problems. Thus, the approximate and accurate representations and solutions can be integrated. That is, to address the how partial solutions of sub-problems can be reintegrated to build a solution for the main problem. The nature of relations between components differs from one decomposition strategy to another. In this paper, we will investigate the possible links and relationships that may appear between sub-problems. , 2015

on_the_relationships_between_sub_problems.pdf

Marouene CHAIEB

, Jaber JEMAI

, Khaled Mellouli

A four-decomposition strategies for hierarchically modeling combinatorial optimization problems: framework, conditions and relations,

We address the problem of modeling combinatorial optimization problems (COP). COPs are generally complex problems to solve. So a good modeling step is fundamental to make the solution easier. Our approach orients researches to choose the best modeling strategy from the beginning to avoid any problem in the solving process. This paper aims at proposing a new approach dealing with hard COPs particularly when the decomposition process leads to some well-known and canonical optimization sub-problems. We tried to draw a clear framework that will help to model hierarchical optimization problems. The framework will be composed by four decomposition strategies which are: objective based decomposition; constraints based decomposition, semantic decomposition and data partitioning strategy. For each strategy, we present supporting examples from the literature where it was applied. But, not all combinatorial problems can be benefit from the outcomes and benefits of modeling problems hierarchically, rather only particular problems can be modeled like a hierarchical optimization problem. Thus, we propose a set of decomposability conditions for decomposing COPs. Furthermore, we define the types of relationships between obtained sub-problems and how partial solutions can be merged to obtain the final solution. , 2015

a_fourdecomposition_strategies_for_hierarchically_modeling_combinatorial_optimization_problems_framework_conditions_and_relations.pdf