Evaluating Multiobjective Evolutionary Algorithms Using MCDM Methods
The evaluation of multiobjective evolutionary algorithms (MOEAs) involves many metrics, it can be considered as a multiple-criteria decision making (MCDM) problem. A framework is proposed to estimate MOEAs, in which six MOEAs, five performance metrics, and two MCDM methods are used. An experimental...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2018-01-01
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| Series: | Mathematical Problems in Engineering |
| Online Access: | http://dx.doi.org/10.1155/2018/9751783 |
| Summary: | The evaluation of multiobjective evolutionary algorithms (MOEAs) involves many metrics, it can be considered as a multiple-criteria decision making (MCDM) problem. A framework is proposed to estimate MOEAs, in which six MOEAs, five performance metrics, and two MCDM methods are used. An experimental study is designed and thirteen benchmark functions are selected to validate the proposed framework. The experimental results have indicated that the framework is effective in evaluating MOEAs. |
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| ISSN: | 1024-123X 1563-5147 |