Termination Criteria in Evolutionary Algorithms: A Survey

Newsha Ghoreishi, Anders Clausen, Bo Nørregaard Jørgensen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Over the last decades, evolutionary algorithms have been extensively used to solve multi-objective optimization problems. However, the number of required function evaluations is not determined by nature of these algorithms which is often seen as a drawback. Therefore, a robust and reliable termination criterion is needed to stop the algorithm. There is a huge amount of knowledge encapsulated in the studies targeting termination criteria in evolutionary algorithms, but an updated integrated overview of this knowledge is missing. For this reason, we aim to conduct a systematic research through a comprehensive literature study. We extended the basic categorization of termination criteria to a more advanced one that takes the most common used termination criteria into consideration based on their specifications and the way they have been evolved over time. The survey is concluded by suggesting a road-map for future research directions.
Original languageEnglish
Title of host publicationProceedings of 9th International Joint Conference on Computational Intelligence
Volume1
PublisherSCITEPRESS Digital Library
Publication date2017
Pages373-384
ISBN (Electronic)978-989-758-274-5
DOIs
Publication statusPublished - 2017
Event9th International Joint Conference on Computational Intelligence - Funchal, Portugal
Duration: 1. Nov 20173. Nov 2017
Conference number: 9

Conference

Conference9th International Joint Conference on Computational Intelligence
Number9
Country/TerritoryPortugal
CityFunchal
Period01/11/201703/11/2017

Keywords

  • Evolutionary Computation
  • Evolutionary Algorithm
  • Termination Criterion
  • Stopping Criterion
  • Convergence
  • Performance Indicator
  • Progress Indicator

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