The Pine Cone Optimization Algorithm (PCOA)
The present study introduces a novel nature-inspired optimizer called the Pine Cone Optimization algorithm (PCOA) for solving science and engineering problems. PCOA is designed based on the different mechanisms of pine tree reproduction, including pollination and pine cone dispersal by gravity and a...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Biomimetics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2313-7673/9/2/91 |
| _version_ | 1827343992294998016 |
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| author | Mahdi Valikhan Anaraki Saeed Farzin |
| author_facet | Mahdi Valikhan Anaraki Saeed Farzin |
| author_sort | Mahdi Valikhan Anaraki |
| collection | DOAJ |
| description | The present study introduces a novel nature-inspired optimizer called the Pine Cone Optimization algorithm (PCOA) for solving science and engineering problems. PCOA is designed based on the different mechanisms of pine tree reproduction, including pollination and pine cone dispersal by gravity and animals. It employs new and powerful operators to simulate the mentioned mechanisms. The performance of PCOA is analyzed using classic benchmark functions, CEC017 and CEC2019 as mathematical problems and CEC2006 and CEC2011 as engineering design problems. In terms of accuracy, the results show the superiority of PCOA to well-known algorithms (PSO, DE, and WOA) and new algorithms (AVOA, RW_GWO, HHO, and GBO). The results of PCOA are competitive with state-of-the-art algorithms (LSHADE and EBOwithCMAR). In terms of convergence speed and time complexity, the results of PCOA are reasonable. According to the Friedman test, PCOA’s rank is 1.68 and 9.42 percent better than EBOwithCMAR (second-best algorithm) and LSHADE (third-best algorithm), respectively. The authors recommend PCOA for science, engineering, and industrial societies for solving complex optimization problems. |
| first_indexed | 2024-03-07T22:40:30Z |
| format | Article |
| id | doaj.art-40e290e18ffa4053b74927fa5bf5bb0e |
| institution | Directory Open Access Journal |
| issn | 2313-7673 |
| language | English |
| last_indexed | 2024-03-07T22:40:30Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomimetics |
| spelling | doaj.art-40e290e18ffa4053b74927fa5bf5bb0e2024-02-23T15:09:05ZengMDPI AGBiomimetics2313-76732024-02-01929110.3390/biomimetics9020091The Pine Cone Optimization Algorithm (PCOA)Mahdi Valikhan Anaraki0Saeed Farzin1Department of Water Engineering and Hydraulics Structures, Faculty of Civil Engineering, Semnan University, Semnan 35131-19111, IranDepartment of Water Engineering and Hydraulics Structures, Faculty of Civil Engineering, Semnan University, Semnan 35131-19111, IranThe present study introduces a novel nature-inspired optimizer called the Pine Cone Optimization algorithm (PCOA) for solving science and engineering problems. PCOA is designed based on the different mechanisms of pine tree reproduction, including pollination and pine cone dispersal by gravity and animals. It employs new and powerful operators to simulate the mentioned mechanisms. The performance of PCOA is analyzed using classic benchmark functions, CEC017 and CEC2019 as mathematical problems and CEC2006 and CEC2011 as engineering design problems. In terms of accuracy, the results show the superiority of PCOA to well-known algorithms (PSO, DE, and WOA) and new algorithms (AVOA, RW_GWO, HHO, and GBO). The results of PCOA are competitive with state-of-the-art algorithms (LSHADE and EBOwithCMAR). In terms of convergence speed and time complexity, the results of PCOA are reasonable. According to the Friedman test, PCOA’s rank is 1.68 and 9.42 percent better than EBOwithCMAR (second-best algorithm) and LSHADE (third-best algorithm), respectively. The authors recommend PCOA for science, engineering, and industrial societies for solving complex optimization problems.https://www.mdpi.com/2313-7673/9/2/91optimizationnature-inspiredpine treepine conemathematical benchmark functionsengineering problems |
| spellingShingle | Mahdi Valikhan Anaraki Saeed Farzin The Pine Cone Optimization Algorithm (PCOA) Biomimetics optimization nature-inspired pine tree pine cone mathematical benchmark functions engineering problems |
| title | The Pine Cone Optimization Algorithm (PCOA) |
| title_full | The Pine Cone Optimization Algorithm (PCOA) |
| title_fullStr | The Pine Cone Optimization Algorithm (PCOA) |
| title_full_unstemmed | The Pine Cone Optimization Algorithm (PCOA) |
| title_short | The Pine Cone Optimization Algorithm (PCOA) |
| title_sort | pine cone optimization algorithm pcoa |
| topic | optimization nature-inspired pine tree pine cone mathematical benchmark functions engineering problems |
| url | https://www.mdpi.com/2313-7673/9/2/91 |
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