Application of the 2-archive multi-objective cuckoo search algorithm for structure optimization
Abstract The study suggests a better multi-objective optimization method called 2-Archive Multi-Objective Cuckoo Search (MOCS2arc). It is then used to improve eight classical truss structures and six ZDT test functions. The optimization aims to minimize both mass and compliance simultaneously. MOCS2...
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Nature Portfolio
2024-12-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-82918-2 |
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| author | Ghanshyam G. Tejani Nikunj Mashru Pinank Patel Sunil Kumar Sharma Emre Celik |
| author_facet | Ghanshyam G. Tejani Nikunj Mashru Pinank Patel Sunil Kumar Sharma Emre Celik |
| author_sort | Ghanshyam G. Tejani |
| collection | DOAJ |
| description | Abstract The study suggests a better multi-objective optimization method called 2-Archive Multi-Objective Cuckoo Search (MOCS2arc). It is then used to improve eight classical truss structures and six ZDT test functions. The optimization aims to minimize both mass and compliance simultaneously. MOCS2arc is an advanced version of the traditional Multi-Objective Cuckoo Search (MOCS) algorithm, enhanced through a dual archive strategy that significantly improves solution diversity and optimization performance. To evaluate the effectiveness of MOCS2arc, we conducted extensive comparisons with several established multi-objective optimization algorithms: MOSCA, MODA, MOWHO, MOMFO, MOMPA, NSGA-II, DEMO, and MOCS. Such a comparison has been made with various performance metrics to compare and benchmark the efficacy of the proposed algorithm. These metrics comprehensively assess the algorithms' abilities to generate diverse and optimal solutions. The statistical results demonstrate the superior performance of MOCS2arc, evidenced by enhanced diversity and optimal solutions. Additionally, Friedman's test & Wilcoxon’s test corroborate the finding that MOCS2arc consistently delivers superior optimization results compared to others. The results show that MOCS2arc is a highly effective improved algorithm for multi-objective truss structure optimization, offering significant and promising improvements over existing methods. |
| format | Article |
| id | doaj-art-d5cdc8ea4bc64c5cb2d3e7bf4a0aa947 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-d5cdc8ea4bc64c5cb2d3e7bf4a0aa9472025-01-05T12:29:11ZengNature PortfolioScientific Reports2045-23222024-12-0114113110.1038/s41598-024-82918-2Application of the 2-archive multi-objective cuckoo search algorithm for structure optimizationGhanshyam G. Tejani0Nikunj Mashru1Pinank Patel2Sunil Kumar Sharma3Emre Celik4Department of Industrial Engineering and Management, Yuan Ze UniversityDepartment of Mechanical Engineering, Faculty of Engineering and Technology, Marwadi UniversityDepartment of Mechanical Engineering, Faculty of Engineering and Technology, Marwadi UniversityDepartment of Information Systems, College of Computer and Information Sciences, Majmaah UniversityDepartment of Electrical and Electronics Engineering, Engineering Faculty, Düzce UniversityAbstract The study suggests a better multi-objective optimization method called 2-Archive Multi-Objective Cuckoo Search (MOCS2arc). It is then used to improve eight classical truss structures and six ZDT test functions. The optimization aims to minimize both mass and compliance simultaneously. MOCS2arc is an advanced version of the traditional Multi-Objective Cuckoo Search (MOCS) algorithm, enhanced through a dual archive strategy that significantly improves solution diversity and optimization performance. To evaluate the effectiveness of MOCS2arc, we conducted extensive comparisons with several established multi-objective optimization algorithms: MOSCA, MODA, MOWHO, MOMFO, MOMPA, NSGA-II, DEMO, and MOCS. Such a comparison has been made with various performance metrics to compare and benchmark the efficacy of the proposed algorithm. These metrics comprehensively assess the algorithms' abilities to generate diverse and optimal solutions. The statistical results demonstrate the superior performance of MOCS2arc, evidenced by enhanced diversity and optimal solutions. Additionally, Friedman's test & Wilcoxon’s test corroborate the finding that MOCS2arc consistently delivers superior optimization results compared to others. The results show that MOCS2arc is a highly effective improved algorithm for multi-objective truss structure optimization, offering significant and promising improvements over existing methods.https://doi.org/10.1038/s41598-024-82918-2ArchiveTrussStructure designPareto dominanceDiversityConvergence |
| spellingShingle | Ghanshyam G. Tejani Nikunj Mashru Pinank Patel Sunil Kumar Sharma Emre Celik Application of the 2-archive multi-objective cuckoo search algorithm for structure optimization Scientific Reports Archive Truss Structure design Pareto dominance Diversity Convergence |
| title | Application of the 2-archive multi-objective cuckoo search algorithm for structure optimization |
| title_full | Application of the 2-archive multi-objective cuckoo search algorithm for structure optimization |
| title_fullStr | Application of the 2-archive multi-objective cuckoo search algorithm for structure optimization |
| title_full_unstemmed | Application of the 2-archive multi-objective cuckoo search algorithm for structure optimization |
| title_short | Application of the 2-archive multi-objective cuckoo search algorithm for structure optimization |
| title_sort | application of the 2 archive multi objective cuckoo search algorithm for structure optimization |
| topic | Archive Truss Structure design Pareto dominance Diversity Convergence |
| url | https://doi.org/10.1038/s41598-024-82918-2 |
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