Publications Internationales

Permanent URI for this collectionhttps://dspace.univ-boumerdes.dz/handle/123456789/13

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Author: search.filters.author.Mellal, Mohamed ArezkiHas files: Yes

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    Multi-objective optimization of series-parallel system with mixed subsystems failure dependencies using NSGA-II and MOHH
    (SAGE, 2024) Mellal, Mohamed Arezki
    In complex systems, failure dependencies play a crucial role in determining their overall performance. This paper explores the multi-objective optimization of series-parallel systems with mixed failure dependencies. By optimizing system cost and availability, the study aims to identify the most efficient redundancy and repair strategies. Two optimization algorithms, the non-dominated sorting genetic algorithm II (NSGA-II) and a novel multi-objective algorithm named the multi-objective hoopoe heuristic (MOHH), are utilized alongside constraint handling techniques to produce Pareto fronts. These fronts illustrate the trade-offs between cost and availability. Additionally, a fuzzy decision method is utilized to determine the best compromise solutions from each optimization technique. Comparing the results, NSGA-II consistently outperforms MOHH in providing better compromise solutions across five independent runs. However, MOHH demonstrates a better standard deviation in its performance.
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    Improvement of system reliability in a natural gas processing facility by PSO and DE
    (Springer Nature, 2024) Saheb, Tafsouthe; Mellal, Mohamed Arezki
    The reliability of the systems as well as its optimization is the first concern of the designers. The elements of a given system can be either in series, parallel, parallel-series, or in a complex configuration. This paper addresses the reliability optimization of a natural gas processing facility. The reliability of this system is calculated and two redundancies strategies, active and standby, are optimized under the resource limits to improve reliability. Two bio-inspired optimization algorithms, namely the particle swarm optimization (PSO) and the differential evolution (DE), are implemented with penalty functions to find the optimal redundancy. The results obtained are compared.
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    Optimal reliability allocation of heterogeneous components in pharmaceutical production plant
    (Springer, 2023) Aqel, Ibrahim; Mellal, Mohamed Arezki
    he COVID-19 pandemic and competitiveness pressure the pharmaceutical companies to acquire systems designed to be as reliable as possible. The present paper aims to optimize the design of a pharmaceutical plant through the reliability allocation of heterogeneous components under the design constraints. The problem is solved by resorting to three nature-inspired algorithms of artificial intelligence (AI): grey wolf optimizer (GWO), shuffled frog-leaping algorithm (SFLA), and adaptive particle swarm optimization (ADAP-PSO). A penalty function is implemented to handle the constraints and the results obtained are compared
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    Resource allocation modeling framework to refactor software design smells
    (2023) Gupta, Priyanka; Anand, Adarsh; Mellal, Mohamed Arezki
    The domain to study design flaws in the software environment has created enough opportunity for the researchers. These design flaws i.e., code smells, were seen hindering the quality aspects of the software in many ways. Once detected, the segment of the software which was found to be infected with such a flaw has to be passed through some refactoring steps in order to remove it. To know about their working phenomenon in a better way, authors have innovatively talked about the smell detection mechanism using the NHPP modeling framework. Further the authors have also chosen to investigate about the amount of resources/efforts which should be allotted to various code smell categories. The authors have developed an optimization problem for the said purpose which is being validated on the real-life smell data set belonging to an open-source software system. The obtained results are in acceptable range and are justifying the applicability of the model
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    Guest editorial : reliability and quality : analysis and applications
    (Emerald Group Holdings, 2022) Bhargava, Cherry; Sharma, Pardeep Kumar; Patil, Rajkumar Bhimgonda; Mellal, Mohamed Arezki
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    Reliability, availability, maintainability, and dependability analysis of Tube-wells Integrated with Underground Pipelines in agricultural fields for irrigation
    (2022) Kumar, Ashish; Saini, Monika; Rajkumar Bhimgonda, Patil; Sameer, Al-Dahidi; Mellal, Mohamed Arezki
    Reliability, Availability, Maintainability, and Dependability (RAMD) study of Tube-wells Integrated with Underground Pipelines (TIUP) is crucial as they are the backbone of the irrigation system. This study is carried out with an objective to perform RAMD analysis, and Failure Modes and Effects Analysis (FMEA) unified with the development of a novel stochastic model using Markovian approach to estimate the Steady-State Availability (SSA) of the TIUP. A real case study of a conventional TIUP system has been performed to validate theoretical and practical results of the proposed model. The failure and repair rates of all subsystems followed exponential distribution, and their impact on system/subsystem’s availability and other reliability measures has been investigated. All the repairs are perfect and random variables associated with failure and repair rates are statistically independent. The centrifugal pump and power supply units are the most critical components as far as reliability and maintainability aspects. The labor also plays a critical role in the operation of the TIUP system
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    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 compared
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    Reliability, maintainability, and availability analysis of a computerized numerical control machine tool using Markov chains
    (Budapest Tech Polytechnical Institution, 2021) Patil, Rajkumar Bhimgonda; Mellal, Mohamed Arezki; Bewoor, Anand K.; Al-Dahidi, Sameer
    eliability, maintainability, and availability analysis of Computerized Numerical Control Machine Tools (CNCMT) is vital as they are widely used in manufacturing industries for mass production. This paper proposes a generalized framework for Time- Between-Failure (TBF) and Time-To-Repair (TTR) data analysis, integrated with Markov chains for estimating the system’s Steady State Availability (SSA). A case study of a typical CNCMT illustrates the applicability and the effectiveness of the proposed framework. The effect of variation of sub-systems' failure and repair rates on the availability of the CNCMT is studied. The critical sub-systems from reliability, maintainability, and availability point of view are identified. The analysis reveals that the CNCMT’s failure and repair rates are nearly constant and the CNCMT fails four times per year. The Lubrication Sub-system (LS) is the utmost severe sub-system as far as maintainability aspect is concerned and Turret Sub-system (TS) is the utmost severe sub-system from a reliability perspective
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    Multi-objective system design optimization via PPA and a fuzzy method
    (Springer, 2021) Mellal, Mohamed Arezki; Salhi, Abdellah
    System design deals with various challenges oftargets and resources, such as reliability, availability,maintainability, cost, weight, volume, and configuration.This paper deals with the multi-objective system avail-ability and cost optimization of parallel–series systems byresorting to the multi-objective strawberry algorithm alsoknown as the Plant Propagation Algorithm or PPA and afuzzy method. It is the first implementation of this opti-mization algorithm in the literature for this kind of problemto generate the Pareto Front. The fuzzy method allowshelping the decision maker to select the best compromisesolution. A numerical case study involving 10 subsystemshighlights the applicability of the proposed approach
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    System reliability-redundancy optimization with cold-standby strategy by an enhanced nest cuckoo optimization algorithm
    (Elsevier Ltd, 2020) Mellal, Mohamed Arezki; Zio, E.
    Three main ways can be followed to design for system reliability, namely component reliability allocation, redundancy allocation (active or standby) and reliability-redundancy allocation. Standby redundancy provides higher reliability than the active one, but its modelling is more complicated. This paper considers the system reliability-redundancy allocation with cold-standby strategy and proposes a new approach to its solution, called enhanced nest cuckoo optimization algorithm (ENCOA). ENCOA uses more realistic procedures than the cuckoo optimization algorithm (COA) in terms of egg laying and survivor cuckoos, based on advanced studies of the European cuckoo's lifestyle available in the literature. Four case studies are investigated in order to highlight the applicability and the performance of the proposed approach. The results are compared to those obtained in previous works of literature