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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Nima, Khodadadi | - |
| dc.contributor.author | Laith, Abualigah | - |
| dc.contributor.author | Qasem, Al-Tashi | - |
| dc.date.accessioned | 2023-04-10T04:33:21Z | - |
| dc.date.available | 2023-04-10T04:33:21Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.uri | https://link.springer.com/article/10.1007/s00521-023-08432-0 | - |
| dc.identifier.uri | https://dlib.phenikaa-uni.edu.vn/handle/PNK/7721 | - |
| dc.description | CC BY | vi |
| dc.description.abstract | The Chaos Game Optimization (CGO) has only recently gained popularity, but its effective searching capabilities have a lot of potential for addressing single-objective optimization issues. Despite its advantages, this method can only tackle problems formulated with one objective. The multi-objective CGO proposed in this study is utilized to handle the problems with several objectives (MOCGO). In MOCGO, Pareto-optimal solutions are stored in a fixed-sized external archive. In addition, the leader selection functionality needed to carry out multi-objective optimization has been included in CGO. The technique is also applied to eight real-world engineering design challenges with multiple objectives. The MOCGO algorithm uses several mathematical models in chaos theory and fractals inherited from CGO. | vi |
| dc.language.iso | en | vi |
| dc.publisher | Springer | vi |
| dc.subject | CGO | vi |
| dc.subject | MOCGO | vi |
| dc.title | Multi-objective chaos game optimization | vi |
| dc.type | Book | vi |
| Appears in Collections | ||
| OER - Công nghệ thông tin | ||
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