A Comparative Study of Genetic and Firefly Algorithms for Sensor Placement in Structural Health Monitoring
Optimal sensor placement (OSP) is an important task during the implementation of sophisticated structural health monitoring (SHM) systems for large-scale structures. In this paper, a comparative study between the genetic algorithm (GA) and the firefly algorithm (FA) in solving the OSP problem is con...
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2015/518692 |
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| author | Guang-Dong Zhou Ting-Hua Yi Huan Zhang Hong-Nan Li |
| author_facet | Guang-Dong Zhou Ting-Hua Yi Huan Zhang Hong-Nan Li |
| author_sort | Guang-Dong Zhou |
| collection | DOAJ |
| description | Optimal sensor placement (OSP) is an important task during the implementation of sophisticated structural health monitoring (SHM) systems for large-scale structures. In this paper, a comparative study between the genetic algorithm (GA) and the firefly algorithm (FA) in solving the OSP problem is conducted. To overcome the drawback related to the inapplicability of the FA in optimization problems with discrete variables, some improvements are proposed, including the one-dimensional binary coding system, the Hamming distance between any two fireflies, and the semioriented movement scheme; also, a simple discrete firefly algorithm (SDFA) is developed. The capabilities of the SDFA and the GA in finding the optimal sensor locations are evaluated using two disparate objective functions in a numerical example with a long-span benchmark cable-stayed bridge. The results show that the developed SDFA can find the optimal sensor configuration with high reliability. The comparative study indicates that the SDFA outperforms the GA in terms of algorithm complexity, computational efficiency, and result quality. The optimization mechanism of the FA has the potential to be extended to a wide range of optimization problems. |
| format | Article |
| id | doaj-art-8990ed81bcb74fb483c82df6f9383946 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-8990ed81bcb74fb483c82df6f93839462025-02-03T01:20:23ZengWileyShock and Vibration1070-96221875-92032015-01-01201510.1155/2015/518692518692A Comparative Study of Genetic and Firefly Algorithms for Sensor Placement in Structural Health MonitoringGuang-Dong Zhou0Ting-Hua Yi1Huan Zhang2Hong-Nan Li3College of Civil and Transportation Engineering, Hohai University, Nanjing 210098, ChinaSchool of Civil Engineering, Dalian University of Technology, Dalian 116023, ChinaCollege of Civil and Transportation Engineering, Hohai University, Nanjing 210098, ChinaSchool of Civil Engineering, Dalian University of Technology, Dalian 116023, ChinaOptimal sensor placement (OSP) is an important task during the implementation of sophisticated structural health monitoring (SHM) systems for large-scale structures. In this paper, a comparative study between the genetic algorithm (GA) and the firefly algorithm (FA) in solving the OSP problem is conducted. To overcome the drawback related to the inapplicability of the FA in optimization problems with discrete variables, some improvements are proposed, including the one-dimensional binary coding system, the Hamming distance between any two fireflies, and the semioriented movement scheme; also, a simple discrete firefly algorithm (SDFA) is developed. The capabilities of the SDFA and the GA in finding the optimal sensor locations are evaluated using two disparate objective functions in a numerical example with a long-span benchmark cable-stayed bridge. The results show that the developed SDFA can find the optimal sensor configuration with high reliability. The comparative study indicates that the SDFA outperforms the GA in terms of algorithm complexity, computational efficiency, and result quality. The optimization mechanism of the FA has the potential to be extended to a wide range of optimization problems.http://dx.doi.org/10.1155/2015/518692 |
| spellingShingle | Guang-Dong Zhou Ting-Hua Yi Huan Zhang Hong-Nan Li A Comparative Study of Genetic and Firefly Algorithms for Sensor Placement in Structural Health Monitoring Shock and Vibration |
| title | A Comparative Study of Genetic and Firefly Algorithms for Sensor Placement in Structural Health Monitoring |
| title_full | A Comparative Study of Genetic and Firefly Algorithms for Sensor Placement in Structural Health Monitoring |
| title_fullStr | A Comparative Study of Genetic and Firefly Algorithms for Sensor Placement in Structural Health Monitoring |
| title_full_unstemmed | A Comparative Study of Genetic and Firefly Algorithms for Sensor Placement in Structural Health Monitoring |
| title_short | A Comparative Study of Genetic and Firefly Algorithms for Sensor Placement in Structural Health Monitoring |
| title_sort | comparative study of genetic and firefly algorithms for sensor placement in structural health monitoring |
| url | http://dx.doi.org/10.1155/2015/518692 |
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