{
  "abstract": "A standardized, elaborate and well-argued performance metric for benchmarking anytime algorithms on noisy optimization problems is missing in the current benchmarking frameworks. This research aims at developing such a metric as an artifact by following the Design Science Research methodology. Existing noise handling practices and benchmarking guidelines are reviewed. Benchmarking experiments, including a test suite containing 13 artificial test functions, were conducted with two state-of-the-art algorithms to assess the performance metric. Based on the experimental results and the existing literature, this study concludes that, rather than relying on a single quantitative value, algorithm performance should be assessed through a comprehensive performance report comprising the numerical loss value, the number of function evaluations, wall-clock runtime, and a performance profile illustrating the trajectory of loss values over time. This approach aims to maximize the reliability, expressiveness, and informational value of performance assessments.",
  "abstract_shown": true,
  "affiliations": [
    "Institute for Information Systems, University of Applied Sciences and Arts Northwestern Switzerland, 4600 Olten, Switzerland"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Ramona Boeh"
    },
    {
      "affs": [
        0
      ],
      "name": "Thomas Hanne",
      "orcid": "0000-0002-5636-1660"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ev6tksmtradr6.bib",
  "cited_by": 0,
  "doi": "10.3390/math14213958",
  "fulltext_url": null,
  "id": "ev6tksmtradr6",
  "issns": [
    "2227-7390"
  ],
  "landing_url": "https://www.mdpi.com/2227-7390/14/21/3958",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [],
  "openalex": null,
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-29",
  "publisher": "MDPI AG",
  "ris": "https://research.draconitic.com/paper/ev6tksmtradr6.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:29Z",
      "native_id": "10.3390/math14213958",
      "source": "crossref",
      "url": "https://www.mdpi.com/2227-7390/14/21/3958"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "issn:2227-7390",
      "subfield": "general"
    }
  ],
  "title": "On the Performance Evaluation of Anytime Algorithms in Noisy Optimization",
  "title_text": "On the Performance Evaluation of Anytime Algorithms in Noisy Optimization",
  "type": "peer-reviewed",
  "updated_at": "2026-10-31T00:20:46Z",
  "url": "https://research.draconitic.com/paper/ev6tksmtradr6",
  "venue": "Mathematics",
  "versions": []
}