---
_id: '46414'
abstract:
- lang: eng
  text: Over the last decades, evolutionary algorithms (EA) have proven their applicability
    to hard and complex industrial optimization problems in many cases. However, especially
    in cases with high computational demands for fitness evaluations (FE), the number
    of required FE is often seen as a drawback of these techniques. This is partly
    due to lacking robust and reliable methods to determine convergence, which would
    stop the algorithm before useless evaluations are carried out. To overcome this
    drawback, we define a method for online convergence detection (OCD) based on statistical
    tests, which invokes a number of performance indicators and which can be applied
    on a stand-alone basis (no predefined Pareto fronts, ideal and reference points).
    Our experiments show the general applicability of OCD by analyzing its performance
    for different algorithmic setups and on different classes of test functions. Furthermore,
    we show that the number of FE can be reduced considerably – compared to common
    suggestions from literature – without significantly deteriorating approximation
    accuracy.
author:
- first_name: Tobias
  full_name: Wagner, Tobias
  last_name: Wagner
- first_name: Heike
  full_name: Trautmann, Heike
  id: '100740'
  last_name: Trautmann
  orcid: 0000-0002-9788-8282
- first_name: Boris
  full_name: Naujoks, Boris
  last_name: Naujoks
citation:
  ama: 'Wagner T, Trautmann H, Naujoks B. OCD: Online Convergence Detection for Evolutionary
    Multi-Objective Algorithms Based on Statistical Testing. In: Ehrgott M, Fonseca
    CM, Gandibleux X, Hao J-K, Sevaux M, eds. <i>Evolutionary Multi-Criterion Optimization</i>.
    Springer Berlin Heidelberg; 2009:198–215. doi:<a href="https://doi.org/10.1007/978-3-642-01020-0_19">https://doi.org/10.1007/978-3-642-01020-0_19</a>'
  apa: 'Wagner, T., Trautmann, H., &#38; Naujoks, B. (2009). OCD: Online Convergence
    Detection for Evolutionary Multi-Objective Algorithms Based on Statistical Testing.
    In M. Ehrgott, C. M. Fonseca, X. Gandibleux, J.-K. Hao, &#38; M. Sevaux (Eds.),
    <i>Evolutionary Multi-Criterion Optimization</i> (pp. 198–215). Springer Berlin
    Heidelberg. <a href="https://doi.org/10.1007/978-3-642-01020-0_19">https://doi.org/10.1007/978-3-642-01020-0_19</a>'
  bibtex: '@inproceedings{Wagner_Trautmann_Naujoks_2009, place={Berlin, Heidelberg},
    title={OCD: Online Convergence Detection for Evolutionary Multi-Objective Algorithms
    Based on Statistical Testing}, DOI={<a href="https://doi.org/10.1007/978-3-642-01020-0_19">https://doi.org/10.1007/978-3-642-01020-0_19</a>},
    booktitle={Evolutionary Multi-Criterion Optimization}, publisher={Springer Berlin
    Heidelberg}, author={Wagner, Tobias and Trautmann, Heike and Naujoks, Boris},
    editor={Ehrgott, Matthias and Fonseca, Carlos M. and Gandibleux, Xavier and Hao,
    Jin-Kao and Sevaux, Marc}, year={2009}, pages={198–215} }'
  chicago: 'Wagner, Tobias, Heike Trautmann, and Boris Naujoks. “OCD: Online Convergence
    Detection for Evolutionary Multi-Objective Algorithms Based on Statistical Testing.”
    In <i>Evolutionary Multi-Criterion Optimization</i>, edited by Matthias Ehrgott,
    Carlos M. Fonseca, Xavier Gandibleux, Jin-Kao Hao, and Marc Sevaux, 198–215. Berlin,
    Heidelberg: Springer Berlin Heidelberg, 2009. <a href="https://doi.org/10.1007/978-3-642-01020-0_19">https://doi.org/10.1007/978-3-642-01020-0_19</a>.'
  ieee: 'T. Wagner, H. Trautmann, and B. Naujoks, “OCD: Online Convergence Detection
    for Evolutionary Multi-Objective Algorithms Based on Statistical Testing,” in
    <i>Evolutionary Multi-Criterion Optimization</i>, 2009, pp. 198–215, doi: <a href="https://doi.org/10.1007/978-3-642-01020-0_19">https://doi.org/10.1007/978-3-642-01020-0_19</a>.'
  mla: 'Wagner, Tobias, et al. “OCD: Online Convergence Detection for Evolutionary
    Multi-Objective Algorithms Based on Statistical Testing.” <i>Evolutionary Multi-Criterion
    Optimization</i>, edited by Matthias Ehrgott et al., Springer Berlin Heidelberg,
    2009, pp. 198–215, doi:<a href="https://doi.org/10.1007/978-3-642-01020-0_19">https://doi.org/10.1007/978-3-642-01020-0_19</a>.'
  short: 'T. Wagner, H. Trautmann, B. Naujoks, in: M. Ehrgott, C.M. Fonseca, X. Gandibleux,
    J.-K. Hao, M. Sevaux (Eds.), Evolutionary Multi-Criterion Optimization, Springer
    Berlin Heidelberg, Berlin, Heidelberg, 2009, pp. 198–215.'
date_created: 2023-08-04T16:15:04Z
date_updated: 2023-10-16T13:58:13Z
department:
- _id: '34'
- _id: '819'
doi: https://doi.org/10.1007/978-3-642-01020-0_19
editor:
- first_name: Matthias
  full_name: Ehrgott, Matthias
  last_name: Ehrgott
- first_name: Carlos M.
  full_name: Fonseca, Carlos M.
  last_name: Fonseca
- first_name: Xavier
  full_name: Gandibleux, Xavier
  last_name: Gandibleux
- first_name: Jin-Kao
  full_name: Hao, Jin-Kao
  last_name: Hao
- first_name: Marc
  full_name: Sevaux, Marc
  last_name: Sevaux
language:
- iso: eng
page: 198–215
place: Berlin, Heidelberg
publication: Evolutionary Multi-Criterion Optimization
publication_identifier:
  isbn:
  - 978-3-642-01020-0
publisher: Springer Berlin Heidelberg
status: public
title: 'OCD: Online Convergence Detection for Evolutionary Multi-Objective Algorithms
  Based on Statistical Testing'
type: conference
user_id: '15504'
year: '2009'
...