Publications Scientifiques
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Item Multi-objective factors optimization in fused deposition modelling with particle swarm optimization and differential evolution(Springer, 2022) Mellal, Mohamed Arezki; Laifaoui, Chahinaze; Ghezal, Fahima; Williams, Edward J.The design of any system contemplates the elaboration of a prototype of the entire system or some parts, before the manufacturing phase. Nowadays, rapid prototyping (RP) is widely used by the designers. Achieving good manufacturing performances needs to handle various process parameters. Most works deal with single objective process parameters. The reality is quite different and the processes involve conflicting objectives. This paper addresses the multi-objective factors optimization of the fused deposition modelling (FDM) technology. The problem is converted into a single one using the weighted-sum method and then solved by resorting to two nature-inspired computing techniques, namely particle swarm optimization (PSO) and differential evolution (DE). The results obtained are comparedItem Optimization of WAG Process Using Dynamic Proxy, Genetic Algorithm and Ant Colony Optimization(Springer, 2018) Nait Amar, Menad; Zeraibi, Noureddine; Kheireddine, RedouaneThe optimization of water alternating gas injection (WAG) process is a complex problem, which requires a significant number of numerical simulations that are time-consuming. Therefore, developing a fast and accurate replacing method becomes a necessity. Proxy models that are light mathematical models have a high ability to identify very complex and non-straightforward problems such as the answers of numerical simulators in brief deadlines. Different static proxy models have been used to date, where a predefined model is employed to approximate the outputs of numerical simulators such as field oil production total (FOPT) or net present value, at a given time and not as functions of time. This study demonstrates the application of time-dependent multi Artificial Neural Networks as a dynamic proxy to the optimization of a WAG process in a synthetic field. Latin hypercube design is used to select the database employed in the training phase. By coupling the established proxy with genetic algorithm (GA) and ant colony optimization (ACO), the optimum WAG parameters, namely gas and water injection rates, gas and water injection half-cycle, WAG ratio and slug size, which maximize FOPT subject to some time-depending constraints, are investigated. The problem is formulated as a nonlinear optimization problem with bound and nonlinear constraints. The results show that the established proxy is found to be robust and an efficient alternative for mimicking the numerical simulator performances in the optimization of the WAG. Both GA and ACO are strongly shown to be highly effective in the combinatorial optimization of the WAG process.Item A game theory approach to solve linear bi-objective programming problems(2017) Bezoui, Madani; Bounceur, Ahcène; Euler, Reinhardt; Moulaï, Mustapha; Djeddi, YoucefItem System reliability and cost optimization under various scenarios using NSGA-III(IEEE, 2020) Chebouba, Billal Nazim; Mellal, Mohamed Arezki; Adjerid, Smail; Benazzouz, DjamelNowadays, industrial systems need to be as reliable as possible in order to ensure safety and competitiveness. This paper addresses the reliabilityredundancy allocation problem (RRAP) of an overspeed protection system in a power plant under various scenarios. Previously, this kind of optimization problems were solved using mathematical programming techniques and considered as a single objective optimization problem, however more recently, bio-inspired algorithms are used to solve this type of optimization problem. In the present work, a multi-objective evolutionary optimization algorithm, called the non-dominated sorting genetic algorithm (NSGA-III) is implemented to solve the problem under a set of nonlinear design constraints. The NSGA-III demonstrates its ability to generate a set of nondominated solutions. The results are discussed under various scenarios of minimum allowable reliabilityItem Multiobjective optimization of an agile machining type linear delta structure(2018) Mansouri, Khaled; Belaidi, Idir; Atia, AbdelmalekThe innovative architectures design of agile machines dedicated to the machining at high speed requires the implementation of analytical and numerical models for the optimization of the kinematic, static and dynamic behavior of the machine, taking into account the elastic deformations and their compensation at level of machine control. In the context of multi-objective optimization, the first part is to identify the parameters and variables inherent to each constituent element of a DELTA robot type machine, the purpose is to optimize the essential elements of its structure. This requires a formulation of the multi-objective problem by expressing the objective functions, the constraints and the corresponding search spaces, as well as the resolution of the problem by the use of high-performance mathematical methods and tools (genetic algorithms, etc.).Item Cost and Availability optimization of Overspeed Protection System in a Power Plant(IEEE, 2019) Mellal, Mohamed Arezki; Chebouba, Billal NazimThis paper addresses the cost and availability optimization of an overspeed protection system in a power plant. The literature has only treated the reliability or cost of this system as a single-objective. Therefore, the multi-objective optimization problem considering the availability and cost is presented. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is applied to generate the Pareto front. The numerical results are discussed under two scenarios of minimum allowable availability.Item An efficient methodology for multi-objective optimization of water alternating CO2 EOR process(Elsevier, 2019) Nait Amar, Menad; Zeraibi, NoureddineItem Optimization of WAG process using dynamic proxy, genetic algorithm and ant colony optimization(Springer, 2018) Nait Amar, Menad; Zeraibi, Noureddine; Redouane, KheireddineItem A game theory approach to solve linear bi-objective programming problems : application to data collection in WSNs(2017) Bezoui, Madani; Bounceur, Ahcène; Euler, Reinhardt; Moulai, MustaphaItem Bi-objective optimization algorithms for joint production and maintenance scheduling : application to the parallel machine problem(Springer, 2009) Berrichi, A.; Amodeo, L.; Yalaoui, F.; Châtelet, E.; Mezghiche, Mohamed