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 language | English |
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Title of host publication | Proceedings of 9th International Joint Conference on Computational Intelligence |
Volume | 1 |
Publisher | SCITEPRESS Digital Library |
Publication date | 2017 |
Pages | 373-384 |
ISBN (Electronic) | 978-989-758-274-5 |
DOIs | |
Publication status | Published - 2017 |
Event | 9th International Joint Conference on Computational Intelligence - Funchal, Portugal Duration: 1. Nov 2017 → 3. Nov 2017 Conference number: 9 |
Conference
Conference | 9th International Joint Conference on Computational Intelligence |
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Number | 9 |
Country/Territory | Portugal |
City | Funchal |
Period | 01/11/2017 → 03/11/2017 |
Keywords
- Evolutionary Computation
- Evolutionary Algorithm
- Termination Criterion
- Stopping Criterion
- Convergence
- Performance Indicator
- Progress Indicator