Multi objective elk herd optimization for efficient structural design
Abstract This research presents an advancement of the Elk Herd Optimization targeting specific real-world multi-objective optimization problems, this algorithm is stated as the multi-objective Elk Herd Optimization (MOEHO). MOEHO exploits reproductive behaviour among elk herds for balancing explorat...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-96263-5 |
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| author | Pinank Patel Divya Adalja Nikunj Mashru Pradeep Jangir Arpita Reena Jangid Gulothungan G Mohammad Khishe |
| author_facet | Pinank Patel Divya Adalja Nikunj Mashru Pradeep Jangir Arpita Reena Jangid Gulothungan G Mohammad Khishe |
| author_sort | Pinank Patel |
| collection | DOAJ |
| description | Abstract This research presents an advancement of the Elk Herd Optimization targeting specific real-world multi-objective optimization problems, this algorithm is stated as the multi-objective Elk Herd Optimization (MOEHO). MOEHO exploits reproductive behaviour among elk herds for balancing exploration and exploitation within the optimization procedure toward diversification and convergence. The algorithm performed better over the set of small-to-medium scale structural design problems thus is widely applicable in engineering design. Further, when compared with eight benchmark truss structures against five well-established algorithms the MOEHO has outperformed them in the perspective of performance parameters like Spacing (SP), Hypervolume (HV) and Inverted Generational Distance (IGD). More concrete statistical analysis through Friedman rank test also ascertains the robustness and efficiency of the algorithm, especially at high complexities in optimization. The research attracts attention to the ability of such an algorithm which maintains a balance between the exploration and exploitation. Computational efficiency of MOEHO and qualitatively diversifying solutions along Pareto front, makes it especially applicable in complex engineering applications. Further research into extension of MOEHO with applicability on more dimensional problems, applied even in energy systems optimization. |
| format | Article |
| id | doaj-art-c46ff1664598478d8fe8d1b49654873a |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-c46ff1664598478d8fe8d1b49654873a2025-08-20T03:07:40ZengNature PortfolioScientific Reports2045-23222025-04-0115113510.1038/s41598-025-96263-5Multi objective elk herd optimization for efficient structural designPinank Patel0Divya Adalja1Nikunj Mashru2Pradeep Jangir3Arpita4Reena Jangid5Gulothungan G6Mohammad Khishe7Department of Mechanical Engineering, Marwadi UniversityDepartment of Mathematics, Marwadi UniversityDepartment of Mechanical Engineering, Marwadi UniversityInnovation Center for Artificial Intelligence Applications, Yuan Ze UniversityDepartment of Biosciences, Saveetha School of Engineering, Saveetha Institute of Medical and Technical SciencesDepartment of CSE, Graphic Era Hill UniversityDepartment of Electronics and Communication Engineering, SRM Institute of Science and TechnologyDepartment of Electrical Engineering, Imam Khomeini Naval Science University of NowshahrAbstract This research presents an advancement of the Elk Herd Optimization targeting specific real-world multi-objective optimization problems, this algorithm is stated as the multi-objective Elk Herd Optimization (MOEHO). MOEHO exploits reproductive behaviour among elk herds for balancing exploration and exploitation within the optimization procedure toward diversification and convergence. The algorithm performed better over the set of small-to-medium scale structural design problems thus is widely applicable in engineering design. Further, when compared with eight benchmark truss structures against five well-established algorithms the MOEHO has outperformed them in the perspective of performance parameters like Spacing (SP), Hypervolume (HV) and Inverted Generational Distance (IGD). More concrete statistical analysis through Friedman rank test also ascertains the robustness and efficiency of the algorithm, especially at high complexities in optimization. The research attracts attention to the ability of such an algorithm which maintains a balance between the exploration and exploitation. Computational efficiency of MOEHO and qualitatively diversifying solutions along Pareto front, makes it especially applicable in complex engineering applications. Further research into extension of MOEHO with applicability on more dimensional problems, applied even in energy systems optimization.https://doi.org/10.1038/s41598-025-96263-5Nature-Inspired AlgorithmMulti-Objective optimization with structurePerformance matricesCompliance |
| spellingShingle | Pinank Patel Divya Adalja Nikunj Mashru Pradeep Jangir Arpita Reena Jangid Gulothungan G Mohammad Khishe Multi objective elk herd optimization for efficient structural design Scientific Reports Nature-Inspired Algorithm Multi-Objective optimization with structure Performance matrices Compliance |
| title | Multi objective elk herd optimization for efficient structural design |
| title_full | Multi objective elk herd optimization for efficient structural design |
| title_fullStr | Multi objective elk herd optimization for efficient structural design |
| title_full_unstemmed | Multi objective elk herd optimization for efficient structural design |
| title_short | Multi objective elk herd optimization for efficient structural design |
| title_sort | multi objective elk herd optimization for efficient structural design |
| topic | Nature-Inspired Algorithm Multi-Objective optimization with structure Performance matrices Compliance |
| url | https://doi.org/10.1038/s41598-025-96263-5 |
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