Quokka swarm optimization: A new nature-inspired metaheuristic optimization algorithm
Metaheuristics are efficient algorithms designed to address a broad spectrum of optimization challenges and offer satisfactory solutions, even in scenarios of limited processing capability or incomplete information. It has been observed that no single metaheuristic algorithm is universally ideal for...
| 出版年: | Journal of Intelligent Systems |
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| 主要な著者: | , |
| フォーマット: | 論文 |
| 言語: | 英語 |
| 出版事項: |
De Gruyter
2024-06-01
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| 主題: | |
| オンライン･アクセス: | https://doi.org/10.1515/jisys-2024-0051 |
| 要約: | Metaheuristics are efficient algorithms designed to address a broad spectrum of optimization challenges and offer satisfactory solutions, even in scenarios of limited processing capability or incomplete information. It has been observed that no single metaheuristic algorithm is universally ideal for all applications. This realization underscores the opportunity for the introduction of new metaheuristic algorithms or enhancements to existing ones. |
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| ISSN: | 2191-026X |