Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences
To solve different kinds of optimization challenges, meta-heuristic algorithms have been extensively used. Population initialization plays a prominent role in meta-heuristic algorithms for the problem of optimization. These algorithms can affect convergence to identify a robust optimum solution. To...
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| Main Authors: | , , , , , , |
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| 格式: | Article |
| 語言: | English English |
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MDPI AG, Basel, Switzerland
2021
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| 在線閱讀: | https://eprints.ums.edu.my/id/eprint/31833/1/Studying%20the%20Impact%20of%20Initialization%20for%20Population-Based%20Algorithms%20with%20Low-Discrepancy%20Sequences.pdf https://eprints.ums.edu.my/id/eprint/31833/2/Studying%20the%20Impact%20of%20Initialization%20for%20Population-Based%20Algorithms%20with%20Low-Discrepancy%20Sequences1.pdf https://eprints.ums.edu.my/id/eprint/31833/ https://www.mdpi.com/2076-3417/11/17/8190 https://www.mdpi.com/journal/applsci |
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https://eprints.ums.edu.my/id/eprint/31833/1/Studying%20the%20Impact%20of%20Initialization%20for%20Population-Based%20Algorithms%20with%20Low-Discrepancy%20Sequences.pdfhttps://eprints.ums.edu.my/id/eprint/31833/2/Studying%20the%20Impact%20of%20Initialization%20for%20Population-Based%20Algorithms%20with%20Low-Discrepancy%20Sequences1.pdf
https://eprints.ums.edu.my/id/eprint/31833/
https://www.mdpi.com/2076-3417/11/17/8190
https://www.mdpi.com/journal/applsci