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CHAIEB Marouene
Marouene
CHAIEB
chaieb.marouene@live.fr
moury.7up@gmail.com
Maître assistant
<p>Departement statistiques et analyses,</p>
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
<p>Combinatorial Optimization Problems; Supply chain management; Operational Research; Decision support systems; Artificial Intelligence.</p>
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
<p>Tache: Conception et implementation d une application de gestion des commandes</p>
Stagiaire a Tunisie Tradenet
01/02/2010-20/05/2010
Tunis
<p>Tache: Conception et implementation d une application d achat en ligne</p>
Stagiaire au Banque Internationale Arabe de Tunisie (BIAT)
07/07/2009-31/08/2009
Tunis
<p>Tache: la conception et l implementation d une application de gestion d integration des modeules de l SAP aux besoin de la banque.</p>
Stagiaire a International Bio Services
01/06/2008-31/06/2008
Tunis
<p>Tache: la conception et l implementation d une application de gestion des materiels informatique.</p>
Stagiaire a International Form
07/07/2008-30/08/2008
Tunis
<p>Tache: la conception et l implementation d une application de gestion de conge avec la notion du work flow</p>
Modules enseignés
Assistant a l ISG
<p>ASD</p>
Assistant a l Universite de Selmen Ibn AbdelAziz
<p>Data Base Computer architecture Software Engineering Operation Systems ICDL</p>
Activités administratives
<p>Chef de departement des statistiques et des analyses de l universite de Sattam Ibn AbdelAziz</p>
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.
<p>ISG de Tunis</p>
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
<p>ISG de Tunis</p>
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...]
<p>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.</p>
Marouene CHAIEB
,
Jaber JEMAI
, Khaled Mellouli
Decomposability Conditions of Combinatorial Optimization Problems,
<p>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.</p>
,
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,
<p>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.</p>
,
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,
<p>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.</p>
,
2015
a_fourdecomposition_strategies_for_hierarchically_modeling_combinatorial_optimization_problems_framework_conditions_and_relations.pdf
Marouene CHAIEB
,
Jaber JEMAI
, Khaled Mellouli
The home care scheduling problem: a modeling and solving issue,
,
2013
the_home_care_scheduling_problem_a_modeling_and_solving_issue.pdf
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