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19 results on '"Chebbo, Nazir"'

1. Preventive Maintenance Optimization and Comparison of Genetic Algorithm Models in a Series–Parallel Multi-State System

Author

Maatouk Imane, Jarkass Iman, Châtelet Eric, and Chebbo Nazir

Subjects
fuzzy logic, genetic algorithm, local search, optimization, preventive maintenance, Science, Electronic computers. Computer science, QA75.5-76.95
Abstract

In this research, different optimization models are developed to solve the preventive maintenance (PM) optimization problem in a maintainable multi-state series–parallel system. The objective is to determine for each component in the system the maintenance period minimizing a cost function under the constraint of required availability and for a specified horizon of time. Four genetic models based on the cost associated with maintenance schedule and availability characteristic parameters are constructed and analyzed. They are genetic algorithm (GA), hybridization GA and local search (GA-LS), fuzzy logic controlled GA (FLC-GA), and hybridization FLC-GA and LS. The experiment analyzes and compares the efficiency between them. These experiments investigate the effect of the parameters of the GA on the structure of optimal PM schedules in multi-state multi-component series–parallel systems. Results show that the hybridization FLC-GA and LS outperform the other algorithms.

Published
2019
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3. Multi-objective design optimisation of repairable k -out-of- n subsystems in series with redundant dependency.

Author

Habib, Milia, Yalaoui, Farouk, Chehade, Hicham, Jarkass, Iman, and Chebbo, Nazir

Subjects
RESOURCE allocation, ENGINEERING design, MULTIDISCIPLINARY design optimization, COST, EVOLUTIONARY algorithms, METAHEURISTIC algorithms
Abstract

Several researches have been investigated on Multi-Objective Redundancy Allocation Problems (MORAPs), but none of them have considered the redundant dependency at the design stage. This latter which is a special kind of failure dependency can affect significantly the system performance. Due to this fact, this paper deals with the multi-objective system design optimisation with dependent components by focusing on two objectives: maximisation of system availability and minimisation of system cost with components choice and weight constraints. A system consisting of manyk-out-of-nrepairable subsystems connected in series is considered. The components of a subsystem are supposed to be identical and may be dependent. They are selected from a set of available component types. In addition to the redundancy level and the number of repair teams allocated to each subsystem, the choice of components type and the dependency level are also considered as decision variables. Since the described problem is NP hard, we propose three multi-objective meta-heuristic algorithms based on Non-dominated Sorting Genetic Algorithm (NSGA II) and Strength Pareto Evolutionary Algorithm (SPEA II) with different constraints handling. An exact method is also applied. To analyse their performances, numerical applications are provided and comparisons based on different well-known metrics are presented. [ABSTRACT FROM AUTHOR]

Published
2017
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4. Multisources of Energy Contracting Strategy with an Ecofriendly Factor and Demand Uncertainties

Author

Hamze, Abbas, Ouazene, Yassine, Chebbo, Nazir, Maatouk, Imane, Université Libanaise, Laboratoire d'Optimisation des Systèmes Industriels (LOSI), Institut Charles Delaunay (ICD), and Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)

Subjects
optimal contract capacity, peak load demand, lcsh:T, [SPI.NRJ]Engineering Sciences [physics]/Electric power, lcsh:Technology, multisources of energy, mathematical programming
Abstract

International audience; This study presents a mathematical formulation to optimize contracting capacity strategies of multisources of energy for institutional or industrial consumers considering demand uncertainties. The objective consists of minimizing the total costs composed of the different types of energy contract capacity costs, penalty price, and an ecofriendly factor. The penalty price is charged on the demand of energy exceeding the total contract capacities. The ecofriendly factor encourages the use of renewable energy and reduces the traditional energy used in the optimal mix of energy sources. The proposed model is tested based on demand of energy inspired from real data. These numerical experiments are analyzed to illustrate the impact of encouraging the use of renewable energy sources by introducing the ecofriendly factor and the influence of penalty price and uncertainty in the demand of energy. The results show that in the presence of low penalty price or low uncertainty a large amount of ecofriendly support is needed for using more renewable energy sources in the optimal contract capacity combination.

Published
2019

6. Availability analysis and redundant dependency modeling of k-out-of-n:G system

Author

Habib, Milia, Yalaoui, Farouk, Chehade, Hicham, Chebbo, Nazir, Jarkass, Iman, Laboratoire d'Optimisation des Systèmes Industriels (LOSI), Institut Charles Delaunay (ICD), Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS), Université Libanaise, and Gavrysiak, Daniel

Subjects
[INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2017

7. Maintenance Optimization Using Fuzzy Logic Controlled Genetic Algorithm

Author

Maatouk, Imane, Chebbo, Nazir, Jarkass, Iman, Chatelet, Eric, Laboratoire Modélisation et Sûreté des Systèmes (LM2S), Institut Charles Delaunay (ICD), Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS), and Université Libanaise

Subjects
[INFO.INFO-PF]Computer Science [cs]/Performance [cs.PF], preventive maintenance, genetic algorithm, Key-Words: -Fuzzy logic, multi-states system, optimization
Abstract

International audience; In the field of reliability management, using preventive maintenance is one of the major operations. Optimizing the maintenance policy is required so as to provide a low-cost and efficient function of the system. This paper deals with the problem of maintenance optimization in a multi-states series-parallel system. The objective is to optimize for each system component the maintenance policy minimizing a cost function of the system under the constraint of required availability and for a specified period. Since inspections in the beginning of the life of a component, when the component is very reliable are not efficient, the maintenance policy should identify the dates of first inspection of each system component. We propose using an evolutionary algorithm called fuzzy logic controlled genetic algorithm (FLC-GA) to solve this optimization problem. Two controllers are used to adaptively adjust the crossover and the mutation probabilities based on the fitness function and on the degree of population diversity. Simulation results are presented for the proposed method which is compared to a genetic algorithm with fixed crossover and mutation probabilities. The experimental results show the advantages and the efficiency of FLC-GA.

Published
2016

9. Optimisation de performances et maîtrise de la fiabilité dans la conception de systèmes de production

Author

Habib, Milia, Chebbo, Nazir, Jarkass, Iman, Chehade, Hicham, Yalaoui, Farouk, LASTRE, Université Libanaise, Laboratoire d'Optimisation des Systèmes Industriels (LOSI), Institut Charles Delaunay (ICD), Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS), and VU VAN, Jean-Baptiste

Subjects
[INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2015

10. Évaluation et optimisation des performances des systèmes de production à la phase de conception

Author

Habib, Milia, Yalaoui, Farouk, Chehade, Hicham, Chebbo, Nazir, Jarkass, Iman, VU VAN, Jean-Baptiste, Laboratoire d'Optimisation des Systèmes Industriels (LOSI), Institut Charles Delaunay (ICD), Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS), and Université Libanaise

Subjects
[INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2014

13. Preventive maintenance optimization for multi-states series-parallel systems

Author

Maatouk, Imane, Chebbo, Nazir, Chatelet, Eric, Laboratoire Modélisation et Sûreté des Systèmes (LM2S), Institut Charles Delaunay (ICD), Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS), and Université Libanaise

Subjects
[INFO.INFO-PF]Computer Science [cs]/Performance [cs.PF], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2013

14. Decisions Making Optimization in a Complex System's Maintenance Policy Using Metaheuristics, UGF and Proportional Hazard Model

Author

Samrout, Mohamad, Chatelet, Eric, Kouta, Raed, Chebbo, Nazir, Laboratoire Modélisation et Sûreté des Systèmes (LM2S), Institut Charles Delaunay (ICD), Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Mécatronique - Méthodes, Modèles et Métiers (IRTES - M3M), Université de Technologie de Belfort-Montbeliard (UTBM)-Institut de Recherche sur les Transports, l'Energie et la Société - IRTES, and Université Libanaise

Subjects
[INFO.INFO-PF]Computer Science [cs]/Performance [cs.PF], Universal Generating Function, preventive maintenance, Metaheuristics, propor- tional hazard, ant colony system
Abstract

International audience; The world is getting increasingly complex and we are becoming more and more depending on man-made systems and environments. Failures and lack of function may have increasing consequences to an increasing number of people. In many areas pressure on cost or use of resources is growing. This is a challenge to every organization-how can available resources be used in an effective way. In this situation maintenance optimization is an ever-present issue. In this paper, an optimized maintenance policy for multi state system is presented. Metaheuristics are used as optimisation tools, and the Universal Generating Function and proportional hazard model in system behaviour modelling.

Published
2007

15. Decisions making optimisation in a complex systems maintenance policy using metaheuristics, UGF and proportional hazard model

Author

Samrout, Mohamad, Chatelet, Eric, KOUTA, Raed, Chebbo, Nazir, Laboratoire Modélisation et Sûreté des Systèmes (LM2S), Institut Charles Delaunay (ICD), Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Mécatronique - Méthodes, Modèles et Métiers (IRTES - M3M), Université de Technologie de Belfort-Montbeliard (UTBM)-Institut de Recherche sur les Transports, l'Energie et la Société - IRTES, and Université Libanaise

Subjects
[INFO.INFO-PF]Computer Science [cs]/Performance [cs.PF]
Abstract

International audience; The world is getting increasingly complex and we are becoming more and more depending on man-made systems and environments. Failures and lack of function may have increasing consequences to an increasing number of people. In many areas pressure on cost or use of resources is growing. This is a challenge to every organization – how can available re-sources be used in an effective way. In this situation maintenance optimization is an ever-present issue. In this paper, an optimized maintenance policy for multi state system is pre-sented. Metaheuristics are used as optimisation tools, and the Universal Generating Function and proportional hazard model in system behaviour modelling.

Published
2006

16. The preventive maintenance cost of series-parallel systems minimization using genetic and ant colony algorithms

Author

Samrout, Mohamed, Yalaoui, Farouk, Chatelet, Eric, Chebbo, Nazir, Modélisation et Sûreté des Systèmes (M2S), Institut des Sciences et Technologies de l'Information de Troyes (ISTIT), Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Optimisation des Systèmes Industriels (LOSI), Institut Charles Delaunay (ICD), and Université Libanaise

Subjects
[INFO.INFO-PF]Computer Science [cs]/Performance [cs.PF], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2004

18. Design optimization and redundant dependency study of series k — out — of — n : Grepairable systems

Author

Habib, Milia, Yalaoui, Farouk, Chehade, Hicham, Chebbo, Nazir, and Jarkass, Iman

Abstract

This paper proposes a new optimization approach to find the best redundancy allocation of dependent repairable series k—out—of—n : Gsystem using ant colony optimization. A model for the failure redundant dependency between the system components is formulated. It is considered in the system performance evaluation. An optimization model is then derived to be solved using the software LINGO and the proposed ACO algorithm. The objective consists of minimizing the system cost while satisfying a required level of system availability. The best system configuration in terms of number of components and number of repair teams in each subsystem is to be determined. The components are characterized by their failure rate, repair rate, unit acquisition cost and unit repair cost. In order to validate the proposed approach, an illustrative example is applied. A comparison between LINGO and ACO results is facilitated. The results show that the redundant dependency may positively affect the design configuration and the system cost. Furthermore, the proposed ACO outperforms LINGO for large scale systems in term of solution quality.

Published
2016
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