Advanced Fruit Fly Optimization Algorithm and Its Application to Irregular Subarray Phased Array Antenna Synthesis
In this paper, an advanced fruit fly algorithm (FOA) is proposed and applied in subarray phased array antenna synthesis. The proposed algorithm introduces orthogonal crossover, quantum selection and simulated annealing operations on the individuals, and then combines them by using an adaptive expans...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8901129/ |
| _version_ | 1828977163913658368 |
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| author | Wentao Li Yudong Zhang Xiaowei Shi |
| author_facet | Wentao Li Yudong Zhang Xiaowei Shi |
| author_sort | Wentao Li |
| collection | DOAJ |
| description | In this paper, an advanced fruit fly algorithm (FOA) is proposed and applied in subarray phased array antenna synthesis. The proposed algorithm introduces orthogonal crossover, quantum selection and simulated annealing operations on the individuals, and then combines them by using an adaptive expansion-contraction factor. Accordingly, a linear generation mechanism of candidate solution based fruit fly algorithm (LGMS-FOA) is generated, in which individuals are selected in a highly balanced way, and the poor solutions are still accepted with a varying probability during the iteration. These mechanisms help the proposed algorithm enhance the population diversity and global searching capability but avoid falling into local optimum. Numerical classical unimodel benchmark functions are provided to test the proposed algorithm (OLFOA) in comparison with other advanced algorithms. In addition, to further validate its superiority, the proposed algorithm is applied to handle the subarray array synthesis of several tough planar and circular apertures with different array sizes and subarray shapes. Simulation results show that the proposed OLFOA can achieve better performance than other improved evolutionary algorithms. |
| first_indexed | 2024-12-14T14:52:14Z |
| format | Article |
| id | doaj.art-6204ac1cc154419f93b0d9ba1627fe61 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T14:52:14Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-6204ac1cc154419f93b0d9ba1627fe612022-12-21T22:57:05ZengIEEEIEEE Access2169-35362019-01-01716558316559610.1109/ACCESS.2019.29535448901129Advanced Fruit Fly Optimization Algorithm and Its Application to Irregular Subarray Phased Array Antenna SynthesisWentao Li0https://orcid.org/0000-0001-6662-5781Yudong Zhang1https://orcid.org/0000-0003-0352-9594Xiaowei Shi2https://orcid.org/0000-0003-4146-9916Department of Electronic Engineering, Science and Technology on Antenna and Microwave Laboratory, Xidian University, Xi’an, ChinaDepartment of Electronic Engineering, Science and Technology on Antenna and Microwave Laboratory, Xidian University, Xi’an, ChinaDepartment of Electronic Engineering, Science and Technology on Antenna and Microwave Laboratory, Xidian University, Xi’an, ChinaIn this paper, an advanced fruit fly algorithm (FOA) is proposed and applied in subarray phased array antenna synthesis. The proposed algorithm introduces orthogonal crossover, quantum selection and simulated annealing operations on the individuals, and then combines them by using an adaptive expansion-contraction factor. Accordingly, a linear generation mechanism of candidate solution based fruit fly algorithm (LGMS-FOA) is generated, in which individuals are selected in a highly balanced way, and the poor solutions are still accepted with a varying probability during the iteration. These mechanisms help the proposed algorithm enhance the population diversity and global searching capability but avoid falling into local optimum. Numerical classical unimodel benchmark functions are provided to test the proposed algorithm (OLFOA) in comparison with other advanced algorithms. In addition, to further validate its superiority, the proposed algorithm is applied to handle the subarray array synthesis of several tough planar and circular apertures with different array sizes and subarray shapes. Simulation results show that the proposed OLFOA can achieve better performance than other improved evolutionary algorithms.https://ieeexplore.ieee.org/document/8901129/Irregular subarrayfruit fly algorithmorthogonal crossingquantum behaviorsimulated annealingarray synthesis |
| spellingShingle | Wentao Li Yudong Zhang Xiaowei Shi Advanced Fruit Fly Optimization Algorithm and Its Application to Irregular Subarray Phased Array Antenna Synthesis IEEE Access Irregular subarray fruit fly algorithm orthogonal crossing quantum behavior simulated annealing array synthesis |
| title | Advanced Fruit Fly Optimization Algorithm and Its Application to Irregular Subarray Phased Array Antenna Synthesis |
| title_full | Advanced Fruit Fly Optimization Algorithm and Its Application to Irregular Subarray Phased Array Antenna Synthesis |
| title_fullStr | Advanced Fruit Fly Optimization Algorithm and Its Application to Irregular Subarray Phased Array Antenna Synthesis |
| title_full_unstemmed | Advanced Fruit Fly Optimization Algorithm and Its Application to Irregular Subarray Phased Array Antenna Synthesis |
| title_short | Advanced Fruit Fly Optimization Algorithm and Its Application to Irregular Subarray Phased Array Antenna Synthesis |
| title_sort | advanced fruit fly optimization algorithm and its application to irregular subarray phased array antenna synthesis |
| topic | Irregular subarray fruit fly algorithm orthogonal crossing quantum behavior simulated annealing array synthesis |
| url | https://ieeexplore.ieee.org/document/8901129/ |
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