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Shock and Vibration
Volume 2015 (2015), Article ID 518692, 10 pages
Research Article

A Comparative Study of Genetic and Firefly Algorithms for Sensor Placement in Structural Health Monitoring

1College of Civil and Transportation Engineering, Hohai University, Nanjing 210098, China
2School of Civil Engineering, Dalian University of Technology, Dalian 116023, China

Received 11 August 2014; Accepted 1 October 2014

Academic Editor: Bo Chen

Copyright © 2015 Guang-Dong Zhou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.