Case Study of Genetic Algorithms in Metrology: Assessment of Inter-laboratory Comparisons
This study reviews conventional consensus estimation methods, including mean-based, median-based, and pooling-based approaches, and evaluates their performance under challenging scenarios involving outliers and deviations from normality. While traditional methods such as the weighted mean and weight...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2025-01-01
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| Series: | EPJ Web of Conferences |
| Online Access: | https://www.epj-conferences.org/articles/epjconf/pdf/2025/08/epjconf_cim2025_14001.pdf |
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| _version_ | 1849738621690576896 |
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| author | Coulon Romain |
| author_facet | Coulon Romain |
| author_sort | Coulon Romain |
| collection | DOAJ |
| description | This study reviews conventional consensus estimation methods, including mean-based, median-based, and pooling-based approaches, and evaluates their performance under challenging scenarios involving outliers and deviations from normality. While traditional methods such as the weighted mean and weighted median often fail to handle extreme values and non-Gaussian distributions, advanced techniques like the Monte Carlo Median (MCM) and Power Moderated Mean (PMM) offer improved robustness. The Genetic Algorithm (GA), a novel optimization-based approach, demonstrates exceptional resilience to outliers. To facilitate its application, the GA is made available through the Python package consensusGen, accessible via the Python Package Index and GitHub. This ensures that practitioners and researchers can easily implement the GA in their consensus estimation tasks, benefiting from its superior robustness and precision. |
| format | Article |
| id | doaj-art-25db73e77df84440b5d0cf18bfe9480e |
| institution | DOAJ |
| issn | 2100-014X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | EPJ Web of Conferences |
| spelling | doaj-art-25db73e77df84440b5d0cf18bfe9480e2025-08-20T03:06:30ZengEDP SciencesEPJ Web of Conferences2100-014X2025-01-013231400110.1051/epjconf/202532314001epjconf_cim2025_14001Case Study of Genetic Algorithms in Metrology: Assessment of Inter-laboratory ComparisonsCoulon Romain0Bureau International des Poids et Mesures, Pavillon de BreteuilThis study reviews conventional consensus estimation methods, including mean-based, median-based, and pooling-based approaches, and evaluates their performance under challenging scenarios involving outliers and deviations from normality. While traditional methods such as the weighted mean and weighted median often fail to handle extreme values and non-Gaussian distributions, advanced techniques like the Monte Carlo Median (MCM) and Power Moderated Mean (PMM) offer improved robustness. The Genetic Algorithm (GA), a novel optimization-based approach, demonstrates exceptional resilience to outliers. To facilitate its application, the GA is made available through the Python package consensusGen, accessible via the Python Package Index and GitHub. This ensures that practitioners and researchers can easily implement the GA in their consensus estimation tasks, benefiting from its superior robustness and precision.https://www.epj-conferences.org/articles/epjconf/pdf/2025/08/epjconf_cim2025_14001.pdf |
| spellingShingle | Coulon Romain Case Study of Genetic Algorithms in Metrology: Assessment of Inter-laboratory Comparisons EPJ Web of Conferences |
| title | Case Study of Genetic Algorithms in Metrology: Assessment of Inter-laboratory Comparisons |
| title_full | Case Study of Genetic Algorithms in Metrology: Assessment of Inter-laboratory Comparisons |
| title_fullStr | Case Study of Genetic Algorithms in Metrology: Assessment of Inter-laboratory Comparisons |
| title_full_unstemmed | Case Study of Genetic Algorithms in Metrology: Assessment of Inter-laboratory Comparisons |
| title_short | Case Study of Genetic Algorithms in Metrology: Assessment of Inter-laboratory Comparisons |
| title_sort | case study of genetic algorithms in metrology assessment of inter laboratory comparisons |
| url | https://www.epj-conferences.org/articles/epjconf/pdf/2025/08/epjconf_cim2025_14001.pdf |
| work_keys_str_mv | AT coulonromain casestudyofgeneticalgorithmsinmetrologyassessmentofinterlaboratorycomparisons |