Many-Objective Cheetah Optimizer: A Novel Paradigm for Solving Complex Engineering Problems Article Swipe
Pinank Patel
,
Divya Adalja
,
Nikunj Mashru
,
Pradeep Jangir
,
Arpita Arpita
,
R. S. Jangid
,
G. Gulothungan
,
Ahmad O. Hourani
,
Kaznah Alshammari
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1007/s44196-025-00859-8
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1007/s44196-025-00859-8
Complex many-objective optimization problems (MaOPs) generate multiple challenges for obtaining convergence alongside diversity within extensive multi-dimensional solution areas. Optimization approaches currently face limitations when trying to balance exploration and exploitation especially when resources become limited. MaOCO represents the Many-Objective Cheetah Optimization Algorithm which draws its concepts from the hunting behavior of cheetahs. MaOCO includes adaptive search functions that use attack and sit-and-wait approaches to optimize exploration and exploitation capabilities. MaOCO produces hypervolume (HV) results that exceed NSGA-III and MaOMVO by 50% while also delivering inverse generational distance (IGD) results which reach 40% better than both competing methods. The algorithm demonstrates superior efficiency in solving complex MaOPs, because it requires lower computational costs by 15%. MaOCO successfully traverses Pareto-optimal fronts according to theoretical evaluations, and its modular structure allows for both scale-up and hybridization features. The implemented applications of this approach include optimizing energy systems along with designing structures for engineering projects. Future researchers plan to integrate MaOCO with additional metaheuristic techniques to improve its performance when dealing with dynamic and irregular Pareto front problems.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s44196-025-00859-8
- https://link.springer.com/content/pdf/10.1007/s44196-025-00859-8.pdf
- OA Status
- gold
- Cited By
- 7
- References
- 44
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4411212572
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https://openalex.org/W4411212572Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1007/s44196-025-00859-8Digital Object Identifier
- Title
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Many-Objective Cheetah Optimizer: A Novel Paradigm for Solving Complex Engineering ProblemsWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2025Year of publication
- Publication date
-
2025-06-11Full publication date if available
- Authors
-
Pinank Patel, Divya Adalja, Nikunj Mashru, Pradeep Jangir, Arpita Arpita, R. S. Jangid, G. Gulothungan, Ahmad O. Hourani, Kaznah AlshammariList of authors in order
- Landing page
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https://doi.org/10.1007/s44196-025-00859-8Publisher landing page
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https://link.springer.com/content/pdf/10.1007/s44196-025-00859-8.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://link.springer.com/content/pdf/10.1007/s44196-025-00859-8.pdfDirect OA link when available
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Computer science, Management science, Industrial engineering, Mathematical optimization, Artificial intelligence, Mathematics, EngineeringTop concepts (fields/topics) attached by OpenAlex
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7Total citation count in OpenAlex
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2025: 7Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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