A multi-agent differential evolution for linear array synthesis
This paper describes a multi-agent differential evolution (MADE) for optimizing linear arrays synthesis. In order to find better solution, each individual of MADE as a agent compete or cooperate with their neighbors, then perform crossover, mutation and selection to diffused global knowledge. And it...
| Main Authors: | , |
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| Format: | Conference Paper |
| Published: |
2010
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| Online Access: | http://hdl.handle.net/20.500.11937/39206 |
| _version_ | 1848755528556085248 |
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| author | Zhao, C. Wu, Changzhi |
| author_facet | Zhao, C. Wu, Changzhi |
| author_sort | Zhao, C. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This paper describes a multi-agent differential evolution (MADE) for optimizing linear arrays synthesis. In order to find better solution, each individual of MADE as a agent compete or cooperate with their neighbors, then perform crossover, mutation and selection to diffused global knowledge. And it is used for optimization to reduce the peak side lobe level (PSLL) with minimum element spicing constraints, through dynamic computing lower bound and upper bound, constraints can be handled. Contrast with other result, MADE has greater efficiency and robustness. © 2010 IEEE. |
| first_indexed | 2025-11-14T08:57:44Z |
| format | Conference Paper |
| id | curtin-20.500.11937-39206 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:57:44Z |
| publishDate | 2010 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-392062017-09-13T14:26:10Z A multi-agent differential evolution for linear array synthesis Zhao, C. Wu, Changzhi This paper describes a multi-agent differential evolution (MADE) for optimizing linear arrays synthesis. In order to find better solution, each individual of MADE as a agent compete or cooperate with their neighbors, then perform crossover, mutation and selection to diffused global knowledge. And it is used for optimization to reduce the peak side lobe level (PSLL) with minimum element spicing constraints, through dynamic computing lower bound and upper bound, constraints can be handled. Contrast with other result, MADE has greater efficiency and robustness. © 2010 IEEE. 2010 Conference Paper http://hdl.handle.net/20.500.11937/39206 10.1109/ICGCS.2010.5543094 restricted |
| spellingShingle | Zhao, C. Wu, Changzhi A multi-agent differential evolution for linear array synthesis |
| title | A multi-agent differential evolution for linear array synthesis |
| title_full | A multi-agent differential evolution for linear array synthesis |
| title_fullStr | A multi-agent differential evolution for linear array synthesis |
| title_full_unstemmed | A multi-agent differential evolution for linear array synthesis |
| title_short | A multi-agent differential evolution for linear array synthesis |
| title_sort | multi-agent differential evolution for linear array synthesis |
| url | http://hdl.handle.net/20.500.11937/39206 |