An Adapted NSGA-II Algorithm for a Reconfigurable Manufacturing System (RMS) Design Under Machines Reliability Constraints

Dahane, Mohammed; Benyoucef, Lyès

doi:10.1007/978-3-319-23350-5_5

Cited by 21 publications

(3 citation statements)

References 37 publications

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“…This fact limits their practical application in industrial settings because in real life, the individual components are never 100% reliable; this means the system as a whole also has a lower than nominal reliability, which directly affects its productivity, efficiency, and production costs [29]. Although in their work [8], Dahane and Benyoucef did draw attention to the issue of reliability in the process of designing RMS, they concentrated solely on the problem of selecting machines for the system under design. Thus, there are no research results showing how a change in the level of reliability of machines affects the level of reliability and expected productivity of an RMS.…”

Section: Introductionmentioning

confidence: 99%

Reliability analysis of reconfigurable manufacturing system structures using computer simulation methods

Gola¹

2018

EiN

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Section: Introductionmentioning

confidence: 99%

Reliability analysis of reconfigurable manufacturing system structures using computer simulation methods

Gola¹

2018

EiN

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“…These approaches have been separately applied to different RMS problems. For example, the application of MOPSO can be found in [43,46], while NSGA-II has been used in [28,38]. Since each algorithm offers certain advantages in computation, the aim is to reinforce the positive aspects of each approach by combining them.…”

Section: Evolutionary Solution Approachesmentioning

confidence: 99%

Modularity-based quality assessment of a disruptive reconfigurable manufacturing system-A hybrid meta-heuristic approach

Khan

Homri

Dantan

et al. 2021

Int J Adv Manuf Technol

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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“…The EAs are commonly classified as metaheuristic algorithms, which are being employed heavily in various Multi-Criteria Decision-Making (MCDM) problems of SET. These include building design and energy efficiency (Brownlee and Wright 2015;Delgarm et al 2016), wireless sensory network design (Hacioglu et al 2016;Murugeswari, Radhakrishnan, and Devaraj 2016), manufacturing system design (Azadeh et al 2017;Dahane and Benyoucef 2016), parametric design of production processes (Li et al 2016), software design, and analysis (Malhotra et al 2018;Mkaouer et al 2015), tuning and feature selection of machine learning techniques (Bouraoui, Jamoussi, and Ayed 2018;Geethanjali, Slochanal, and Bhavani 2008) etc.…”

Section: Introductionmentioning

confidence: 99%

A Collaborative Beetle Antennae Search Algorithm Using Memory Based Adaptive Learning

Ghosh

Martinsen

2021

Applied Artificial Intelligence

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Recently developed Beetle Antennae Search algorithm (BAS) mimics the odor sensing mechanism of the longhorn beetles. The beetles have many species and many of these are advantageous to the nature as well as the mankind. Excepting the odor sensing activity, the beetles are naturally strong insects, and some of them have storage memory for adaptive learning and showcase social behavior. These natural mechanisms make them intelligent enough to perform the routine tasks for existence. This article proposes a novel Storage (Memory) Adaptive Collaborative BAS (SACBAS) algorithm, which incorporates the memory stored adaptive learning. This helps exploit the Group Extreme Value (GEV) instead of the Individual Extreme Values in swarm for faster convergence. Further, the SACBAS uses the reference points based on non-dominated sorting to diversify the state space. To test the data-driven performance of SACBAS, the Support Vector Machine (SVM) algorithm with linear kernel is used in this study. First, the SACBAS algorithm is tested on the multi-objective ZDT and DTLZ test-suites and compared with two recent techniques, the reference points based Nondominated Sorting Genetic Algorithm (NSGA III) and Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D). Second, the data-driven SACBAS is tested with realworld cases based on offline data. The proposed SACBAS is shown to handle the offline data efficiently and obtains promising results. The Friedman Test is carried out to differentiate the SACBAS from other two techniques and the Post Hoc Test confirms that the SACBAS obtains better HyperVolume indicator scores and outperforms the NSGA III and MOEA/D.

show abstract

An Adapted NSGA-II Algorithm for a Reconfigurable Manufacturing System (RMS) Design Under Machines Reliability Constraints

Cited by 21 publications

References 37 publications

Reliability analysis of reconfigurable manufacturing system structures using computer simulation methods

Reliability analysis of reconfigurable manufacturing system structures using computer simulation methods

Modularity-based quality assessment of a disruptive reconfigurable manufacturing system-A hybrid meta-heuristic approach

A Collaborative Beetle Antennae Search Algorithm Using Memory Based Adaptive Learning

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