Operational Research and Decision Mathematics Laboratory (LROMAD)
LAROMAD Laboratory
Our teams
Team 01: GRAPHICS AND ORDERS
Team Leader: Dr SADI Bachir
Area: Graphs - Orders
Description of the team's research theme:
The aim of classification is to organize data. The modeling of knowledge and data, and their exploitation for the extraction, deduction and prediction of information for the decision problem, are major aspects of artificial intelligence, or "data mining". One of the aims of data analysis is to extract information from a database. Our team's aim is to carry out an in-depth study of a set of problems posed by existing knowledge extraction algorithms, and to make improvements. Formal concept analysis, introduced by R. Wille of Darmstadt, offers a formal tool whose central notion is the concept lattice. This method has proved inapplicable in the case of large databases, since the size of the lattice can be exponential. The notion of an implication system introduced by Duquenne, which is an interpretation of lattices, seems to us to be a good direction for this problem. Indeed, the knowledge extraction problem can be reduced to the generation of a system of implications. We propose to explore the properties of the representation of a system of implications through the notion of the "core" of a lattice, which is a minimal representation of a system of implications.
Team 02: Optimal Control and Optimization
Team Leader: Dr OUKACHA Brahim
Area: Optimal Control-Optimization
Keyword: Graphs, recognition, algorithmic, object generation, algorithmic complexity, invariant computation, order, partial order, Support, Control, Command, Optimality, adapted method, semi-Infinite, convex, global optimization, optimums, Branch and Bound, Regulation, fluidity, sliding mode control, traffic, transportation,
Team 03: Global Optimization and Semi-Infinite Optimization
Team Leader: Dr OUANES Mohand
Domain: Global Optimization - Semi-infinite Optimization
Description of the team's research theme
Global optimization has developed considerably in recent years, thanks in particular to the power of computing resources. Classical methods only give local solutions (except in the convex case). Global optimization methods calculate global optimums. Global optimization is concerned with the quality of the solution in the non-convex case. The methods used are in the spirit of combinatorial optimization, but applied to the continuous case (Branch and Bound, cuts, etc....). Fields of application include: engineering, electrical design, chemistry, etc.....
A semi-infinite optimization problem is a mathematical program with a finite number of variables and an infinite number of constraints. The methods used are : Discretization, cuts, SQP method, and c..... The fields of application are Air pollution abatement, integrated circuits, Chebyshev approximation, etc.
Team members
| Name | First name | Last diploma | grade | |
OUANES | MOHAN | State doctorate | Professor | |
CHEBBAH | MOHAMED | Magistère | MAA | |
LESLOUS | FADILA | Magistère | MAA | |
GOUMEZIANE | LYNDA | Magistère | MAA | |
MESSAOUDENE | KARIMA | Magistère | MAA |
Complete list of doctoral students in the team
| First and last name | Registered since | Name and surname of supervisor(s) |
| AMROUCHI ZAHIA | September 2014 | Ouanes Mohamed and Frideric Messine |
| MAMAR SAMIA | September 2013 | Ouanes Mohamed |
| DROUCHE HAKIMA | September 2017 | Ouanes Mohamed |
| KHERBOUCHE LYNDA | September 2018 | Ouanes Mohamed |
Team 04: Stochastic multicriteria optimization and urban traffic
Team Leader: Dr BELLAHCENE Ep RABIA Fatima
Domain: Stochastic multicriteria optimization-Urban traffic
Key word: Regulation, fluidity, sliding mode control, traffic, transport.
Description of the team's research theme:
Our aim is to develop and implement algorithms for solving environmental, economic and urban traffic problems. In the field of urban traffic (transport), we need to define a criterion that translates our control objective into terms of partial differential equations. This criterion must be expressed in terms of the control variables, and must aim to improve travel time while ensuring fluidity of flow. Several avenues can be explored, including constrained optimal control of nonlinear systems, sliding mode control, etc.
Team members
| First and last name | Last diploma | Grade | Domaine | |
BELLAHCENE EP RABIA Fatima | HABILITATION | M.C.A | Mathematics | |
ZERDANI EP BOUARAB Ouiza | HABILITATION | M.C.A | Mathematics | |
SMAIL RABAH | Magistère | MAA | Mathematics |
